PRELIMINARY PERFORMANCE ANALYSIS OF S&P BSE 500 SHARIAH INDEX

1 naayGuS ISSN - 0975-4032 Volume VI/VII Issue II / I July - Dec. 2013 / Jan. - June 2014 Global Impact Factor (GIF) for 2012 - 0.421 & 2013 - 0.493 RESEARCH ARTICLES Shivani Nischal & G.S. Bhalla Exploring the Predictive Power of OSCM Model of Conflict Management towards Work Productivity- A Comparative Approach between Public and Private Sector Banks Suyam Praba. R & Malarmathi. B Determinants of Households decisions and influence of Cultural and Demographic factors on Investment Decision Making - An Empirical study among Salaried Investors Parag Rijwani Investigating Mutual Fund Performance Persistence Pardhasaradhi Madasu Preliminary Performance Analysis of S&P BSE 500 Shariah Index Meenakshi Tyagi & Renu Sharma Impact of Inflation on Economic Factors in Indian Economy BOOK REVIEW Pavan Patel & K.V.S. Krihna Mohan I / II eussI ,IIV / IV emuloV The Challenges of Indian Management Chief Patron: Mrs. S. Aarathy President and CEO Siva Sivani Group of Institutions, Secunderabad. Patron: Mr. Sailesh Sampathy Vice President and Deputy CEO Siva Sivani Group of Institutions, Secunderabad. Editor: Dr. V. G. Chari Assistant Vice President Siva Sivani Institute of Management. Assistant Editor: Dr.Kompalli Sasi Kumar Associate Professor, Finance Area Siva Sivani Institute of Management. Editorial Advisory and Review Panel Dr. Ashish Sadh, Professor, Marketing area, IIM Indore Dr. Cullen Habel, Lecturer in Marketing, The University of Adelaide Business School, South Australia Prof. Anantha S Babbili, Professor in Media and Communication, Texas A&M Univeristy, Corpus Christi. Dr. C. Gopalkrishnan, Director & Professor of Strategic Management, Institute of Management, Nirma University, Ahmedabad Dr. H.K. Jayavelu, Professor- HR, IIM K Dr. Prashanth N Bharadwaj, Dean’s Associate and Professor, Indiana University of Pennsylvania, USA Dr. B. Rajashekar, Reader, School of Management Studies, University of Hyderabad, Dr. RajendraNargundkar, Director, MDI , Gurgaon Dr.A.Sudhakar, Professor & Registarar, Department of Commerce, Dr.B.R.A.O.U, Hyderabad. Dr. G.B. Reddy, Associate Professor, Department of law, Osmania University, Hyderabad Dr. S.M. Vijaykumar, Professor - OB & HRM,Chairperson - Research & Ph.D. IMT Nagpur Dr. Yerram Raju. B, Regional Director, PRMIA, Hyderabad Dr. Shahaida .P, Associate Professor –Marketing, ASCI, Hyderabad Prof. V. Venkaiah, Professor and Head, Department of Business Management, Dr. B. R. Ambedkar Open University Dr. M. Kamalakar, Professor - Operations and IT & EVP, SSIM Dr. V. G. Chari, Professor – Finance & AVP, SSIM Dr. P.V. S. Sai, Director, Training and Consultancy, SSIM Dr. S. F. Chandrashekar, Professor - HR, SSIM Dr. S.V.Ramana Rao, Professor –Finance & Director -Academic, SSIM Prof. Muralidhar Rao, Professor – Marketing, SSIM. Dr. K. S. Harish, Associate Professor - QT, SSIM. Contents Title Page # RESEARCH ARTICLES Exploring the Predictive Power of OSCM Model of Conflict Management towards Work Productivity- A Comparative Approach between Public and Private Sector Banks – Shivani Nischal & G.S. Bhalla 5 Determinants of Households decisions and influence of Cultural and Demographic factors on Investment Decision Making - An Empirical study among Salaried Investors – Suyam Praba. R & Malarmathi. B 19 Investigating Mutual Fund Performance Persistence – Parag Rijwani 28 Preliminary Performance Analysis of S&P BSE 500 Shariah Index – Pardhasaradhi Madasu 42 Impact of Inflation on Economic Factors in Indian Economy – Meenakshi Tyagi & Renu Sharma 50 BOOK REVIEW The Challenges of Indian Management – Pavan Patel & K.V.S. Krihna Mohan 59 Copyright: Siva Sivani Institute of Management, Secunderabad, India. SuGyaan is a bi-annual publication of the Siva Sivani Institute of Management, NH-7, Kompally, Secunderabad- 500 100. All efforts are made to ensure correctness of the published information. However, Siva Sivani Institute of management is not responsible for any errors caused due to oversight or otherwise. The views expressed in this publication are purely personal judgments of the authors and do not reflect the views of Siva Sivani Institute of Management. All efforts are made to ensure that published information is free from copyright violations. However, authors are personally responsible for any copyright violation. 4 SuGyaan Editorial... It gives me immense pleasure in presenting before you the combined issues of Volume VI/ VolumeVII, Issue II/ Issue-I- July-Dec,2013/ Jan-June, 2014 of Sugyaan Management Journal of Siva Sivani Institute of Management. In its fifth year of existence Sugyaan has received a tremendous response from its readers and contributors. Our sincere gratitude to the readers, authors and reviewers for their support. In our continuous effort to contribute to the cause of nation building by promoting quality research through thought provoking ideas in the form of research papers, articles, case studies and book reviews we, in the current issue of Sugyaan, have included six papers from different disciplines viz., Marketing, Accounts, Finance, Economics, Insurance, Human Resource, followed by a book review. The first paper titled "Exploring the Predictive Power of OSCM Model of Conflict Management towards Work Productivity - A Comparative Approach between Public and Private Sector Banks", by ShivaniNischal&G.S.Bhalla, used the pre-tested structured questionnaire based upon UdaiPareek's model i.e. OSCM (Opinion Survey on Conflict Management) and 9-item work performance instrument based upon Minnesota Satisfactoriness Scale (MSS Scale) has been utilized under the study. They concluded that significant impact of conflict management strategies upon the work performance of the employees in these selected public and private sector banks under study. The second paper titled, "Determinants of Households decisions and influence of Cultural and Demographic factors on Investment decision making - An empirical study among Salaried Investors", by SuyamPraba&Malarmathi.K, examined the relationship between the cultural factors like religion, mother tongue, the demographical factors like age, gender, education, life stage, marital status, occupation, work experience, the reference group and investment decision making in households. They concluded that there is a significant associations between these cultural and demographical factors on household investment decision maker. The third paper titled "Investigating Mutual Fund Performance Persistence" by ParagRijwani analyzed the short run persistence performance of equity diversified growth mutual funds based on three major empirical tests: contingency table analysis of winners and losers, chi-squared independence testing on these tables and Ordinary Least Square (OLS) regression analysis of returns. The study indicated that there is significant performance persistence in mutual fund returns. This outcome is true for both the lowest performing and highest performing mutual funds. The fourth paper titled "Preliminary Performance Analysis of S&P BSE 500 Shariah Index by Pardhasaradhimadasu", addressed the Islamic Finance Industry trends and practices with the help of a proxy by name Shariah Index. Performance of Shariah Index was analyzed against S&P BSESensex, S&P BSE-100, S&P BSE-500 and concluded that there is a strong correlation presents between various indices. The fifth research paper titled "Impact of Inflation on Economic Factors in Indian Economy", by Meenaskhi andRenu Sharma examined the impact of inflation on various economic factors viz., economic growth, investment and household saving rate. They concluded that Inflation has a negative effect on growth but positive effect on investment and household savings. Lastly, we have a book review, "The Challenges of Indian Management" by Pavan Patel and K.V.S. Krishnamohan. We hope you find this issue interesting and look forward to your feedback. Volume VI / VII, Issue II / I 5 SuGyaan Exploring the Predictive Power of OSCM Model of Conflict Management towards Work Productivity -A Comparative Approach between Public and Private Sector Banks *ShivaniNischal and ** Dr. G.S. Bhalla ABSTRACT Conflict exists throughout environments of all kinds. Although conflict management is complex and sometimes hard to achieve, a greater understanding of the behavioural skills associated with it can have a bottom line impact on work performance as well as organisational productivity. This research paper actually attempts to explore the significant predictors of OSCM model of conflict management upon work performance or productivity in comparative form among the public and private sector banks selected under the scope of the study. For the purpose of study, the sample includes 365 bank managers from twenty commercial banks situated in Amritsar, Jalandhar and Ludhiana cities of Punjab. Ten banks each from public sector and private sector has been selected on the basis of highest number of employees (Prowess Software and annual reports of these banks March, 2013). The pre-tested structured questionnaire based upon UdaiPareek’s model i.e. OSCM (Opinion Survey on Conflict Management) and 9-item work performance instrument based upon MSS Scale has been utilized under the study. Various statistical techniques have been employed such as reliability and validity analysis, descriptive statistics, weighted average scores, Bi-variate correlation analysis, simple regression and multiple regression analysis. Overall the findings revealed the significant influence of two main modes of OSCM model of conflict management upon the work performance of the employees in both public sector and private sector banks and it shakes the employees’ performance at significance level. Keywords: Conflict Management Strategies: Resignation, Withdrawal, Negotiation, Confrontation, Compromise, Arbitration, Appeasement and Defusion; Work Performance and Public& Private Sector Commercial Banks. JEL Classification Code : D74 1. Introduction “Although conflict management is complex and sometimes hard to achieve, a greater understanding of the behavioural skills associated with it can have a bottom line impact on organisational productivity.” -Vincent L. Ferraro and Sheila A. Adams Conflict is defined as disagreement between individuals. It can vary from mild disagreements to a win-or-lose, emotion-packed, confrontation (Kirchoff and Adams, 1982). Conflict can be a serious problem in an organisation. It can create chaotic conditions that make it nearly impossible for employees to work together. Thomas and Scmidt have reported that managers spend 20% of their time in dealing with conflict situations. Hence it is very much important that managers should understand the serious consequences of conflict in organisation so that they can find out techniques to deal with the relative dysfunctional impacts of conflicts. Conflict resolving approaches have been suggested by various academicians and experts such as Blake & Mouton’s Managerial Grid (1964), Thomas &Killman’s MODE (1976), Rahim’s Conflict Resolving Mechanism (1982), Pareek (1982), Knudson, Sommers& Golding, (1980); Billingham& Sack, (1987), Sillars, (1980); Putnam & Wilson, (1982), four Smyth, (1977); Phillips &Cheston, (1979), (Sternberg & Soriano, (1984); Morrill & Thomas, (1992), Nicotera, (1993); Pareek, (1982) and Kindler, (1996) to handle or manage conflict. Pareek (1982) proposed a contingency model of managing conflict in the organisations. This model consists of avoidanceapproach mode to handle or manage conflict.Rahim’s (1983) model ROCI-II had been developed for the measurement of five styles of *Senior Research Fellow, Department of Commerce & Business Management, Guru Nanak Dev University, Amritsar (143001), Punjab, India, Ct: 8427009718, [email protected].; ** Professor, Department of Commerce & Business Management, Guru Nanak Dev University, Amritsar (143001), Punjab, India. Volume VI / VII, Issue II / I 6 SuGyaan inter-personal conflicts such as Accommodating, Collaborating, Compromising, Avoiding &Competing and further research should be needed in the diagnosis of styles of handling interpersonal conflict between the employees of organisation. Further, Rahim et al. (2001) explored the relationship between conflict handling styles and job performance of employees. The findings revealed the positive significant influence of conflict handling modes upon job performance of employees. Rahim and Psenicka (2004) further investigated the moderating or mediating effects of various strategies of the conflict management upon job performance with significant and positive relationships in outcomes. Rahim (2010) in his research article “Functional and Dysfunctional strategies for managing conflict” revealed that employees who used functional conflict management strategy attained high level of job performance than employees who used dysfunctional style of conflict management. The study stressed upon the usage of only functional strategy of conflict management because of its significant association with better job performance and organisational citizenship behaviour. Obasan (2011) reviewedconsequential effects of conflict and its management upon corporate productivity with the motive of suggesting a valid conclusion to banking industry. Results revealed the significant positive relationships of work performance and conflict resolving mechanism adopted in selected banks under study. Rashid et al. (2012) developed regression model of conflict handling approaches and investigated the impact of conflict management upon team performance. The study analysed that how team members adjust with conflict through appropriate conflict management approach and how the particular conflict handling mode impact the effectiveness of team. Data has been gathered from 240 employees of public and private sector higher organisations. The results amazed that the conflict handling methods had a significant positive influence upon the team performance. This research paper has been divided into several sections. Firstly; the analysis section deals with studying the overall impact of conflict management strategies upon the work performance of the employees; thereby further sections deal with analysing significantly the impact of avoidance and approach modes of handling conflict upon the work performance of private sector and public sector bank employees. Concluding observations has been discussed in the final section. Approach mode of conflict management model includes confrontation, negotiation, arbitration and compromise strategies whereas Avoidance mode includes resignation, withdrawal, appeasement and defusion strategies to handle conflict in the organisation. 2. Objectives and Research Methodology: Fig. 1 Approach-Avoidance Styles of Conflict Management (Pareek’s OSCM Model, 1982) (Source: Training Instruments in HRD & OD by Pareek 2012) Volume VI / VII, Issue II / I 7 SuGyaan The main objectives of research paper are to explore the significant predictors of OSCM model of conflict management upon work performance or productivity in comparative form among the public and private sector banks selected under the scope of the study. Further, the sample of the study includes 365 bank managers from twenty commercial banks selected each from Amritsar, Jalandhar and Ludhiana economical well off cities of Punjab. Ten banks each from public sector and private sector has been selected on the basis of highest number of employees (Prowess Software and annual reports of these banks March, 2013). Convenience cum Judgement sampling technique had been chosen for the purpose of study. The pre-tested structured questionnaire based upon UdaiPareek’s model i.e. OSCM (Opinion Survey on Conflict Management) has been utilized under the study and work performance of employees has been measured with the help of 9-item Minnesota satisfactoriness scale (MSS Scale) (Dewis, Gibson, Lofquist& Weiss 1970).Hypothesis has been tested empirically through various statistical techniques such as descriptive statistics, weighted average scores, Bi-variate correlation analysis, simple regression and multiple regression analysis. The findings revealed the significant influence of two main modes i.e. approach and avoidance mode of OSCM model of conflict management upon the work performance of the employees in both public sector and private sector banks selected under study. 3. Conflict Resolution Mechanism Adopted in Selected Public and Private Sector Banks For the purpose under study, the measurement OSCM scale was first put to reliability test and cronbach’s alpha was calculated. It came out to be 0.71, which was considered satisfactory (Nunnally& Bernstein, 1994). As shown in table no.1, the mean scores of all the constructs of the statements concerning conflict management strategies has been specified and construct validity has been computed with the help of cronbach’s alpha for each construct or conflict management strategy; that comes out to be greater than 0.60 for each construct. This satisfies the construct validity of the OSCM scale undertaken for the research purpose. Table no.1 depicted the descriptive statistics of various conflict management strategies across public sector banks and private sector banks in comparative form. Table -1 Weighted Average Scores and Rank Orderings based on WAS of Opinion Survey on Conflict Management I (OSCM Model)in Public & Private Sector Banks Coding Variables Public Sector (N=181) Private Sector (N=184) Combine Results (N=365) WAS Rank WAS Rank WAS Rank RR_1 Resignation Strategy (α=0.649) 2.84 8 3.62 4 3.22 5 WW_2 Withdrawal Strategy (α=0.706) 2.93 7 2.40 8 2.66 8 NN_3 Negotiation Strategy (α=0.61) 4.00 1 4.09 1 4.04 1 CC_4 Confrontation Strategy (α=0.675) 3.71 3 3.76 3 3.73 4 MM_5 Compromise (α=0.696) 3.97 2 3.61 5 3.79 2 TT_6 Arbitration Strategy (α=0.703) 3.69 4 3.84 2 3.76 3 AA_7 Appeasement Strategy (α=0.65) 3.23 6 2.77 6 3.00 6 DD_8 Defusion Strategy (α=0.692) 3.31 5 2.43 7 2.87 7 Overall Cronbach’s alpha (á) =0.71; [Public Sector Banks under sample: State Bank of India, Punjab National Bank, Canara Bank, Bank of Baroda, Bank of India, Central Bank of India, Union Bank of India, Syndicate Bank and Indian Overseas Bank; Private Sector Banks under sample: ICICI Bank, HDFC Bank, AXIS Bank, Kotak Mahindra Bank, Jammu & Kashmir Bank, ING Vysya Bank, Indusind Bank, Karnataka Bank, South Indian Bank and KarurVysya Bank] Volume VI / VII, Issue II / I 8 SuGyaan The results (table no.1) indicated that public sector bank managers used to follow Negotiation style or strategy mostly to handle conflict with (WAS=4.00); which is further followed by Compromise style (WAS=3.97); Confrontation style (WAS=3.71); Arbitration style (WAS=3.69); Defusion style (WAS=3.31); Appeasement style (WAS=3.23); Withdrawal style (WAS=2.93) and Resignation style (WAS=2.84) of handling conflict with their respective weightage average scores. Where in private sector, bank managers mostly follow Negotiation strategy to handle conflict with WAS=4.09; followed by Arbitration style (WAS=3.84); Confrontation style (WAS=3.76); Resignation style (WAS=3.62); Compromise style (WAS=3.61); Appeasement style (WAS=2.77); Defusion style (WAS=2.43) and Withdrawal style (WAS=2.40) of handling conflict with their respective weightage average scores. Results indicated that managers of public and private sector banks both prefer to negotiate first to resolve conflict in their relative concerns. Managers of both public and private sector banks are least concerned to follow withdrawal strategy and defusion strategy to handle conflict. Ranks based on weighted average scores have been specifically made a clear cut demarcation of the various strategies or styles preferred by the managers of selected public, private sector banks and overall banks. The indicated results (table no.1) revealed that Negotiation style ranks first followed by Compromise style; Confrontation style; Arbitration; Appeasement style; Defusion style; Withdrawal style and Resignation style of handling conflict in public sector banks whereas in private sector banks, Negotiation ranks first followed by Arbitration style; Confrontation style; Resignation style; Compromise style; Appeasement style; Defusion style and Withdrawal style of handling conflict. 4. Work Performance Instrument (MSS Scale) Adopted in Public and Private Sector Banks The mean score and standard deviation for all statements of work performance scale has been depicted in table no.2 showing the results of public sector, private sector and combined areas in comparative form. The measurement scale was put to reliability test and cronbach’s alpha was calculated. The calculated value came out to be 0.628, which was considered satisfactory scale. The results indicated that the private sector employees are good performers (WAS=3.56) but the public sector bank employees are average or intermediate performers (WAS=3). The overall combined results depicted the average performance (overall WAS=3.20) of the employees working in these selected banks under study. (Table 2) 5. Relationship between OSCM Model of Conflict Management and Work Performance Instrument Further moving towards main objective of the study i.e., to analyse the significant impact of conflict management upon work performance of employees in the selected public and private sector banks. First of all, Bi-variate correlation analysis has been applied to check the strength of association between conflict management and work performance variables; then regression analysis has been applied to predict the significance of the predictor variable i.e. conflict management towards dependent variable i.e. work performance. Correlations analysis demonstrated the significant results in private sector banks and public sector banks. From the table no.3, the sign of coefficient of correlation shows the direction of relationship i.e. positive relationship which denotes that there is positive correlation exists between conflict management strategies and work performance of the employees working in these public and private sector banks. (Table 3) 5.1 Simple Regression Analysis With the help of correlation analysis one can only comment upon the association of relationship between the variables but the degree of dependence can only be calculated with the help of regression analysis i.e. change in dependent variable (work performance) with the help of change in independent variable (conflict management). Table no.4 displays the results of simple regression model for work performance with single predictor variable i.e., conflict Management. In table no.4, R square statistic is measure of Volume VI / VII, Issue II / I 9 SuGyaan Table 2 : Descriptive Statistics of Statements of Work Performance Scale (MSS Scale) Variables Combined Results Mean S.D. Private sector Mean S.D. Public Sector Mean S.D. WP1 3.54 1.434 4.17 .974 2.91 1.545 WP2 3.51 1.457 4.10 1.097 2.91 1.536 WP3 3.29 1.472 3.72 1.296 2.86 1.517 WP4 3.27 1.444 3.47 1.414 3.08 1.451 WP5 3.15 1.520 3.69 1.386 2.61 1.459 WP6 3.55 1.420 3.73 1.323 3.38 1.495 WP7 2.15 1.235 2.21 1.184 2.08 1.284 WP8 2.29 1.300 2.85 1.444 1.73 .816 WP9 4.05 1.022 4.13 .924 3.97 1.110 WAS 3.20 Valid N (Listwise) 3.56 365 2.83 184 181 Overall Cronbach’s alpha (α) = 0.628, n=365 Volume VI / VII, Issue II / I 10 SuGyaan extent to which the total variation of the dependent variable (work performance) is explained by the independent variable (conflict management). A high value of R square in regression model explain the variation in the dependent variable i.e. work performance, very well. A large unexplained variation in the regression model will increase the standard errors Model Development Dependent Variable Independent Variable Work Performance Conflict Management The Regression equation for the study would be: Y= e Where, Y=Dependent Variable (Work Performance Score); X= Independent Variable (Conflict Management Score); α=Intercept/Constant; β= Slope & e=error term. of the coefficient. The adjusted R2 tells how well the regression model generalizes. The value of adjusted R2 came out to be 0.426 which indicates that 42.60 percent of the total variation in the dependent variable (work performance) has been explained by independent variable (conflict management). Hence the model is a good fit. An assumption of normal distribution has also been tested with the help of normal probability curve and histograms. F-statistics is mean square (regression) divided by the mean square (residual). ANOVA, i.e. Analysis of variance has been performed to test the overall significance of model. Hence the hypothesis has been tested: H0: β=0. The table no.4 depicted the value of fstatistic=271.652** (p<0.01) i.e. highly significant. Higher the value of F statistic signifies that it is a good regression model predicting outcomes. The higher value of f-statistic (f=271.652**) denotes its significance and Volume VI / VII, Issue II / I SuGyaan rejection of null hypothesis stated above. Further, table no.5 displays the regression coefficients for regression equation of work performance with single predictor variable i.e. conflict management. The value of intercept came out to be 0.878 and the Column B depicted the value of regression coefficient for predicting the dependent variable that is 0.753. The value of regression coefficient indicates that work performance variable change by 0.753 units for every unit change in conflict management variable. So, the conflict management is very much important to be focused upon in order to increase the work performance of the employees working in these selected banks under study and the sign of regression coefficient is positive that means conflict management and work performance variables are positively related. The regression equation would be framed as: Y= 0.878+0.753X+e Where, Y=Dependent Variable (Work Performance Score) and; X= Independent Variable (Conflict Management Score) Simple regression analysis displayed the significance of overall regression model (f=271.652**) and value of adjusted R2 is 0.426 that indicates total 42.60% of variation in the work performance of the employees has been explained by the independent variable i.e. conflict management. Overall the regression model is good fit. At last, Null Hypothesis (H01) that there is insignificant impact of conflict management upon the work performance of the overall bank employees has been rejected and alternate hypothesis has been accepted which clearly demonstrated the positive significant impact of conflict management upon the work performance of the overall bank employees. 11 5.2 Impact of Approach Mode and Avoidance Mode of Handling Conflict upon Work Performance Before formulating the model of regression, Pearson Correlations have been computed to study the association of relationship between the various modes of handling conflict i.e. approach mode (includes negotiation, compromise, confrontation and arbitration); avoidance mode (includes resignation, withdrawal, defusion and appeasement) and work performance variable. Bivariate correlation has been applied and variables have been found statistically significant at 0.01 level of significance. From the table no.6, the sign of coefficient of correlation shows the direction of relationship i.e. positive relationship which denotes that there is positive correlation between approach mode (includes negotiation, compromise, confrontation and arbitration); avoidance mode (includes resignation, withdrawal, defusion and appeasement) strategies of handling conflict in the banks and work performance of the employees working in these public and private sector banks. (Table 6) 5.2.1 Multiple Regression Analysis- Private Sector Scenario Multiple regression has been applied to predict the significance of the several predictor variables towards dependent variable. Multiple regression has been applied in order to ascertain the significant predictors of OSCM model of conflict management towards work performance. So in this section, multiple regression analysis has been performed in order to study the impact of avoidance and approach mode of handling conflict upon work performance of private sector bank employees. Volume VI / VII, Issue II / I SuGyaan The summary of multiple regression model has been depicted in table no.7. The value of R i.e. correlation between approach mode, avoidance mode and work performance come out to be 0.671. The value of adjusted R2 came out to be 0.444 which indicates that 44.40 percent of the total variation in the dependent variable (work 12 performance) has been explained by independent variables i.e. avoidance mode of handling conflict and approach mode of handling conflict. The difference between the values of R2 and adjusted R2 (0.450-0.444=0.006) is very less that means the model will give very less variations in the outcome if it is to be taken from universe rather than from Volume VI / VII, Issue II / I SuGyaan sample. Hence the model is a good fit. Before the application of regression analysis, the problem of multicollinearity has to be checked otherwise results of regression analysis will be damaged. Multicollinearity is a serious problem in regression analysis and occurs when two or more independent variables are highly correlated. (Table 7) a. Predictors: (Constant), Avoidance Mode of Conflict Management, Approach Mode of Conflict Management; b. Dependent Variable: Work Performance Score (Table 8) In the current research, correlation matrix has been generated and no serious problem of multicollinearity has been found. This correlation matrix is a powerful tool to judge about the relationship between variables under study. The suggested rule by Gujrati, 2008 is that if correlation coefficient between two regressors is greater than 0.80, then the problem of 13 multicollinearity is found very serious. Another way to check the problem of multicollinearity is VIF i.e. Variance Inflation Factor, its value should be below 10 as per rule of thumb but if the value exceeds (>10) which mean correlation coefficient is greater than 0.80 and multicollinearity is there. But in our present analysis, no variable has been found whose variance inflation factor exceeds 10 (Table no.8). Toleration value is a measure of correlation between dependent variable and predictor variables and it can vary between 0 to 1 toleration value closer to 0 signify stronger relationship between the regressors and dependent variable. But the variables should not have low tolerance level otherwise this will pose the problem of multicollinearity if the value goes less than 0.20. Hence no problem of multicollinearity has been found in the present analysis. The table no.7 depicted the value of fstatistic=73.946** (p<0.01) i.e. highly significant. Higher the value of F statistic signifies Volume VI / VII, Issue II / I 14 SuGyaan that it is a good regression model predicting outcomes. The higher value of f-statistic (f=73.946**) denotes its significance and rejection of null hypothesis stated above and concludes that one or more partial regression coefficients have a value ‘“0. The value of á=1.060 and the Column B depicted the regression coefficients for predicting the dependent variable that are 0.564 in case of avoidance mode of conflict management and 0.192 in case of approach mode of conflict management. The partial regression coefficients ‘B’ depicted that work performance variable changed by 0.564 unit and 0.192 unit for every unit change in avoidance mode variable and approach mode variable respectively. This indicates that avoidance mode and approach modes of handling conflict are very important to be focused upon in order to increase the work performance of the employees working in these selected private sector banks under study and the sign of regression coefficient is positive that means these avoidance and approach modes are positively related with work performance as dependent variable. Further moving towards the framing of regression equation, i.e.: Y= 1.060+0.564X1+0.192X2+e Where, Y=Dependent Performance Score) Variable (Work X1= Independent Variable 1(Avoidance Mode of handling Conflict) X2= Independent Variable 2(Approach Mode of handling Conflict) Multiple regression analysis displayed the significance of overall regression model (f=73.946**) and adjusted R 2 is 0.444 that indicated 44.40% variation in the work performance of the employees has been explained by the independent variables i.e. i.e. avoidance mode of handling conflict and approach mode of handling conflict. Overall the regression model is good fit. At last, both null hypothesis [H02 & H03] that there is insignificant impact of avoidance mode of handling conflict and approach mode of handling conflict upon the work performance of the private sector bank employees has been rejected and alternate hypothesis has been accepted. 5.2.2. Multiple Regression Analysis- Public Sector Scenario In this section, multiple regression analysis has been performed in order to study the impact of avoidance and approach mode of handling conflict upon work performance of public sector bank employees. Volume VI / VII, Issue II / I 15 SuGyaan a. Predictors: (Constant), Avoidance Mode of Conflict Management, Approach Mode of Conflict Management; b. Dependent Variable: Work Performance Score The summary of multiple regression model has been given in table no.9. The value of adjusted R2 came out to be 0.405 indicates that 40.50 percent of the total variation in the in the dependent variable (work performance) explained by independent variables i.e. avoidance mode of handling conflict and approach mode of handling conflict. The difference between the values of R2 and adjusted R2 (0.411-0.405=0.006) is very less that means the model will give very less variations in the outcome if it is to be taken from universe rather than from sample. Hence the model is a good fit. Before the application of regression analysis, the problem of multicollinearity has been checked and no serious problem of multicollinearity has been found (table no.10). Higher the value of F statistic signifies that it is a good regression model predicting outcomes. The higher value of f-statistic (f=62.194**) denotes its significance and rejection of null hypothesis stated above and concludes that one or more partial regression coefficients have a value # 0. (Table 10) Further, table no.10 displays the regression coefficients for regression equation of work performance with two predictor variables i.e. approach mode and avoidance mode of handling conflict. The value of α=1.031 and the Column B depicted the regression coefficients for predicting the dependent variable that are 0.544 in case of avoidance mode of conflict management and 0.203 in case of approach mode of conflict management. The partial regression coefficients ‘B’ depicted that work performance variable changed by 0.544 unit and 0.203 unit for every unit change in avoidance mode variable and approach mode variable respectively. This indicated that avoidance mode and approach modes of handling conflict are very important to be focused upon in order to increase the work performance of the employees working in these selected public sector banks under study and the sign of regression coefficient is positive that means these avoidance and approach modes are positively related with work performance as dependent variable. Further moving towards the framing of regression equation, i.e.: Y= 1.031+0.544X1+0.203X2+e Where, Y=Dependent Performance Score) Variable (Work Volume VI / VII, Issue II / I 16 SuGyaan X1= Independent Variable 1(Avoidance Mode of handling Conflict); X2= Independent Variable 2(Approach Mode of handling Conflict) Hence, the overall regression model is good. Multiple regression analysis displayed the significance of overall regression model (f=62.194**) and adjusted R 2 is 0.405 that indicated 40.50% of the total variation in the work performance of the employees has been explained by the independent variables i.e. i.e. avoidance mode of handling conflict and approach mode of handling conflict. Overall the regression model is good fit. At last, both null hypothesis [H04 & H05] that there is insignificant impact of avoidance mode of handling conflict and approach mode of handling conflict upon the work performance of the public sector bank employees has been rejected and alternate hypothesis has been accepted which clearly demonstrated the positive significant impact of avoidance mode and approach mode of handling conflict upon the work performance of the public sector bank employees. So, concluding observations states the significant positive relationships of conflict management in public and private sector banks towards work performance. If workplace conflict has been managed properly, it will automatically improve the work performance of the employees as well as enhance organisational productivity. 6. Concluding Observations This research paper mainly deals with comparative data analysis related to exploration of the significant impact of OSCM Model of conflict management upon work performance in selected public and private sector banks under study. Hypothesis (H01 to H05) has been tested empirically through various statistical techniques such as descriptive statistics, weighted average scores, Bi-variate correlation analysis, simple regression and multiple regression analysis. Overall results indicated significant impact of conflict management strategies upon the work performance of the employees in these selected public and private sector banks under study. Avoidance and Approach; both modes of handling conflict are found significant and valid predictors of work performance of in selected public and private sector banks. Further, summary has been given below concentrating towards major description of accepted hypothesis and results obtained (table no.11). 7. Limitations, Suggestions and Managerial Implications The present research work is incapable to plug all the possible sources of errors and contaminations just because of shortage of time and resources, also very likely to produce the genuine results. In the light of above findings, Effective conflict management is necessary both in public as well as in private sector banking organisations. Healthy approaches should be followed up by identifying particularly the nature, types, level and extent of conflict in these banks along with its sources and dysfunctional impacts. Management should have open communication policy so that human resources can come closer, collaborate and make compromises where possible with the authorities concerned. Organisational functionaries should make efforts to conduct seminars and workshops on organisational conflict from time to time for the bank employees. It will help employees’ learning about conflict and its management which in turns helpful in enhancing individual and organisational productivity. If the workplace conflict is managed properly then it helps the management to achieve its strategic objectives with the better work performance of banking staff; positive working environment that will automatically leads towards high organisational productivity. REFERENCES 1. Adebile, O. and Ojo, T. (2012), “Management of organizational conflict in Nigeria Polytechnics, an empirical study of the Federal Polytechnic, Ede Osun State”, International Journal of Asian Social Science, Vol.2, No.3, pp. 229-243. 2. Bezrukova, K., Ramarajan, L., Jehn, K.A. and Euwema, M. (2003), “The Role of Conflict Management Styles and Content-Specific Training across Organisational Boundaries”, Volume VI / VII, Issue II / I 17 SuGyaan retrieved from, http://webpages.scu.edu/ftp/ bezrukova/bezrukov/14249c.doc%20%20best%20paper%20proceedings. doc%20KATE.doc. 5. Nunnally, J. and Bernstein, I. (1994), Psychometric Theor y, McGraw Hill Humanities/Social Sciences/Languages, 3rd edition, pp. 251-261. 3. Bose, K. and Pareek, U. (1986) “The dynamics of conflict management styles of the bankers”, Indian Journal of Industrial Relations, July, Vol.22, No.1, pp. 59-78. 6. 4. Islamoglu, G., Boru, D. and Birsel, M, (2008), “Conflict management styles in relation to demographics”, Bogazici Journal, Vol. 22, No. 2, pp. 107-140. Obasan, K. A. (2011), “Impact of Conflict Management on Corporate productivity: An evaluative study”, Australian Journal of Business and Management Research, August, Vol. 1 No. 5, pp. 44-49. 7. Pareek, U. (1982), Preventing & Resolving Conflicts, San Diego: University Associates, pp. 164-169. Volume VI / VII, Issue II / I SuGyaan 8. Pareek, U. (2012), Training Instruments in HRD and OD, Tata McGraw-Hill Publishing Company Limited, New Delhi. 9. Rahim et al. (2001), “A Structural Equations Model of Leader Power, Subordinates’ Styles of Handling Conflict, and Job Performance”, International Journal of Conflict Management, Vol.12, No. 3, pp. 191-211. 10. Rahim, A. and Psenicka, C., (2004), “Conflict Management strategies as moderators or mediators of the relationship between intragroup conflict and job performance”, Presented at annual conference of the International Association for Conflict Management, Pittsburgh, PA, June, pp. 1518. 11. Rahim, A. (1983), “A Measure of Styles of handling Interpersonal Conflict”, The Academy of Management Journal, Vol. 26, No. 2, pp. 368-376. 12. Rahim, A. (2010), “Functional and Dysfunctional Strategies for Managing 18 Conflict”, paper retrieved from http:// papers.ssrn.com/sol3/papers.cfm? abstract_id=1612886, accessed on Febuary 10th, 2014. 13. Rashid, S, Habib, A. and Toheed, H. (2012), “Effect of Conflict Handling Approaches on team performance: A study on Higher Education”, European Journal of Business and Management, Vol. 4, No. 12, pp. 96-100. 14. Riaz, M. K., Jamal, W. (2012), “Ethnic Background and Conflict Management Styles Preferences”, paper presented at 4th South Asian International Conferences (SAICON) retrieved from http://papers.ssrn.com/sol3/ papers.cfm?abstract_id=2187185, accessed on Febuary 10th, 2014. 15. Thomas K. W. and Schmidt W. H. (1976), “A survey of managerial interests with respect to conflict”, The Academy of management Journal, Vol. 19, No.2, pp. 315-318. # MJ SSIM VI(II) & VII (I) 1, 2014 Volume VI / VII, Issue II / I 19 SuGyaan Determinants of Households Decisions and Influence of Cultural and Demographic Factors on Investment Decision Making – An Empirical Study among Salaried Investors *Suyam Praba.R and **Malarmathi .B. ABSTRACT This study provides us with an insight on investment decision making in Households. There are various factors influencing the investment decisions like cultural, demographical, social, economical factors. This study attempts to identify the relationship between the cultural factors like religion, mother tongue, the demographical factors like age, gender, education, life stage, marital status, occupation, work experience, the reference group and investment decision making in households. 405 samples from salaried class respondents were considered for the study. The Chi square test result shows that there are significant associations between these cultural and demographical factors on household investment decision maker. JEL Classification Code : D14 1. INTRODUCTION Household Investment decision maker could be an individual, the individuals’ spouse, the individual’s parents or any other members of the family. There are various studies conducted to understand the impact of marriage on investment decisions, gender difference on investment decisions, occupation on investment decisions and investment decisions during different life stage. Investment behaviour is a complex study is dependent on various variables and degree of impact of these variables would change from time to time. Hence this study is aimed to understand who makes the investment decisions in a family and the impact of decision making on the individual’s investment pattern. 2. REVIEW OF LITERATURE There is an expanding body of literature that documents evidence of decisions that influence investment decision-making. Barber and Odean (2001) specifically document that overconfidence affects male trading and investment behaviour. Correspondingly, they show that marriage ameliorates some of the behavioural biases males express with respect to investment decisions. Most any person with a sibling of a different gender can attest to the fact that occasionally specific parental decisions seem to be influenced by the gender of the child affected by the decision. Many elements of family structure have been linked to aspects of financial decision making behaviour (see, for example, Smith and Ward, 1980; Browning, 1992; Hao, 1996; Keister, 2003). Smith and Ward (1980) find that young children depress savings for young families but increase savings for marriages of duration greater than 5 years. The principal channel through which children act to reduce savings is the decline in female earnings associated with the child-induced withdrawal of wives from the labour force. In another research study by Nava Ashraf “Spousal Control and Intra-Household Decision Making: An Experimental Study in the Philippines Harvard Business School” found that household savings and investments typically depend on how decision making power distributed between men and women. It also analyzed the fact that, financial decisions of the household are greatly affected by the fact that the income is known to spouses or not. Dev Raj Acharya, Jacqueline S Bell, PadamSimkhada, Edwin R van Teijlingen and Pramod Raj Regmi in the study of ‘ Determinants of Women’s Autonomy in Decision Making’(2010) aimed to explore the links between women’s household position and their autonomy in decision making. M. Hemanta Meitei in the study titled ‘Education or Earning and Access to Resources Determining Women’s Autonomy: An Experience among Women of Manipur’ * Research Scholar, Bharathiar School of Management and Entrepreneur Development, Bharathiar University, Coimbatore, Tamil Nadu, India.; **Professor, School of Management and Entrepreneur Development, Bharathiar University, Coimbatore, Tamil Nadu, India. Volume VI / VII, Issue II / I 20 SuGyaan investigated how far education or earning and access to resources have a significant impact on women’s decision making power. He concluded that, most of the decisions are taken jointly (both husband and wife) while working women take more of independent decisions than the nonworking women. Controlling effect of the other background variables work status of women turn out a significant explanatory variable rather education. 3. NEED FOR THE STUDY This research is done to study the influence of investment decision making on the pattern of investment. The preference and selection of appropriate investment avenues the best suits their investment objective is determined by various influencing factors. One such factors aims for the study is the investment decision maker in a family. The investment decision making could be influenced religion, mother tongue, age, marriage, education, occupation, life stage etc. The research seeks information to find out specifically what influences the investment decisions and their investment process. 4. OBJECTIVE OF THE STUDY
To analyse the impact of culture of individual investors on their Investment decision making.
To analyze the influence of Individual’s demographic factors on Investment decision making 5. HYPOTHESES H10: There is no significant relationship between age and household investment decisions H20: there is no significant relationship between gender and household investment decisions H30: there is no significant relationship between education and household investment decisions H40: there is no significant relationship between marital status and household investment decisions H50: there is no significant relationship between life stage and household investment decisions H60: there is no significant relationship between occupation and household investment decisions H70: there is no significant relationship between work experience and household investment decisions 6. RESEARCH METHODOLOGY This study presents the impact of individual’s cultural and demographic factors on investment behaviour. Keeping this in mind, a schedule was created among the salaried class individual who work either for a Bank, NBFC, Insurance Company, Mutual Fund, IT, ITES, or for Education institutions. In this study, 405 samples were considered based on the Krejcie& Morgan sampling table. It is a Multistage random sampling method is used for the study. The investment details were obtained using a structure questionnaire. The study was conducted in Coimbatore city and the data collection process took place during November 2012 to May 2013. 7. ANALYSIS AND INTERPRETATION It is inferred from the table no: 7.1 that Chi Square test results shows there is significant association between Household Investment decisions and the investors’ age, gender, education, marital status, life stage, occupation, work experience and most influential person for investment. It is also inferred that there is no association between Household Investment decisions and the Investors’ religion, mother tongue, SEC classification and the most preferred Investment Avenue. H10: There is no significant relationship between age and household investment decision making From the Table No. 7.1, it is inferred that the p value is 0.000 which is lesser than 0.05 (5% level of significance) hence the null hypothesis is rejected. Therefore there is significant relationship between age and Household investment decisions.It is evident from the Table No.7.2 that 47.2% of respondents whose age which is lesser than 25 group state that their parents take all investment related decisions. 45.3% of respondents of 26-30 age group and 60% of the respondents of 35 years state they make self decision on Investment. 29.2% of 31-35 age group respondents state their spouse make Investment decisions. Volume VI / VII, Issue II / I SuGyaan 21 Volume VI / VII, Issue II / I SuGyaan H20: There is no significant relationship between Gender and Household investment decisions From the Table No. 7.1, it is inferredthat the p value is 0.000 which is lesser than 0.05 (5% level of significance) hence the null hypothesis is rejected. Therefore there is significant relationship between gender and Household investment decisions. It is evident from the Table No 7.3 that 53.8% of male respondents make self 22 decision on all investment decisions, whereas 33.7% of female respondents have mentioned that their parents take all investment related decisions. H30: There is no significant relationship between Education and Household investment decisions From the Table No. 7.1, it is inferred that the p value is 0.000 which is lesser than 0.05 (5% level of significance) hence the null hypothesis is rejected. Therefore there is significant Volume VI / VII, Issue II / I SuGyaan relationship between education and Household investment decisions.Table No. 7.4 shows that 55.6% of respondents whose diploma holders have responded that their spouse decide on investment. 45.3% of respondents who have completed bachelor degree of education and 50% of respondents who are professionals state that they make self decisions on investments. 36.7% of the respondents who have completed master degree state their parents make Investment decisions. H40: There is no significant relationship between Marital Status and Household investment decisions. From the Table No. 7.1, it is inferred that the p value is 0.000 which is lesser than 0.05 (5% level of significance) hence the null hypothesis is rejected. Therefore there is significant relationship between Marital Status and Household investment decisions. From the Table No. 7.5, it is evident that 48.4% of respondents who are single and 100% of those who are widowed have mentioned that their parents make 23 investment related decisions in their family. 51.6% of respondents who are married and 66.7% of divorced, take self decisions on investments. H50: There is no significant relationship between Life stage and Household investment decisions From the Table No. 7.1, it is inferredthat the p value is 0.000 which is lesser than 0.05 (5% level of significance) hence the null hypothesis is rejected. Therefore there is significant relationship between Life stage and Household investment decisions. It is inferred from the Table No.7.6, that 48.1% of respondents who are single and 26.8% of respondents who are young couple without children have mentioned that their parents make investment related decisions in their family. 36.0% of respondents who are in the life stage – young family with mortgage/childcare cost their spouse make investment related decisions in their family. 60.0% of those who in the stage mature family and 64.7% of those preparing for their retirement take self decisions on investments. Volume VI / VII, Issue II / I SuGyaan H60: There is no significant relationship between Occupation and Household investment decisions From the Table No. 7.1, it is inferred that the p value is 0.026 which is lesser than 0.05 (5% level of significance) hence the null hypothesis is rejected. Therefore there is significant relationship between Occupation and Household investment decisions. It is inferred from the Table No. 7.7 that 63.5% of respondents who work in bank and 50.6% of respondents who work in NBFC take self decisions on investments. 30.0% who work in Insurance Company state their spouse make investment decisions in their family. 36.9% of respondents, who work in IT/ITES Company, and 34.8% of respondents who work in Educational institution and 29.4% of 24 respondents who work in Mutual Fund Company, state their parents take investment decisions in their family. H70: There is no significant relationship between Work Experience and Household investment decisions From the Table No. 7.1, it is inferred that the p value is 0.000 which is lesser than 0.05 (5% level of significance) hence the null hypothesis is rejected. Therefore there is significant relationship between Work experience and Household investment decisions. It is inferred from the Table No.7.8 that 43.1% of respondents whose work experience is below 5 years state their parents take investment decisions in their family. 21.2% of respondents whose work experience is Volume VI / VII, Issue II / I 25 SuGyaan between 5 years to 10 years and 27.3% of the respondents whose work experience is between 15 to 20 years state their spouse make all investment decisions in their family. 62.5% of respondents whose work experience is between 10 to 15 years and 75% of those with 20-25 years of work experience take self decisions on investments. 8. FINDINGS • • There is significant association between Household Investment decisions and the investors’ age, gender, education, marital status, life stage, occupation, work experience, most influential person for investment, Youngster (age < 25 years) state their parents make investment decisions in their family, middle aged respondents state self decisions are done on Investments, while elder respondents claim their spouse as investment decision makers in family. • Men mostly make self decisions on Investments, while women state their parents make investment decisions in their family. • Diploma holders state their spouse while post graduates state their parents about the Investment decisions in their family. Undergraduates and professionals claim to make self decisions on investment. • Respondents who are unmarried and those widowed state their parents make investment related decisions in their family. Married Volume VI / VII, Issue II / I 26 SuGyaan respondents and also those divorced respondents state take self decisions on investments. • • Respondents who are single and respondents in the Life stage - young couple without children have mentioned that their parents make investment related decisions in their family. Respondents who are in the life stage – young family with mortgage/childcare cost their spouse make investment related decisions in their family. Respondents who in the life stage - mature family and also those preparing for their retirement take self decisions on investments. self decisions on investments. Respondents who work in Insurance Company state their spouse make investment decisions in their family. Respondents, who work in IT/ITES Company, Educational institution or Mutual Fund Company, state their parents take investment decisions in their family. • Respondents whose work experience is below 5 years state their parents and those between 5 years to 10 years state their spouse make all investment decisions in their family. Respondents whose work experience is between 10 to 15 years and 20-25 years take self decisions on investments. Respondents who work in bank or NBFC take Volume VI / VII, Issue II / I 27 SuGyaan 9. CONCLUSION In modern era, families getting scattered to nuclear from the traditional extended family type but still we find family values are imbibed in the Indian household culture. It is vital to know the factors influencing the investment decision making within households. It is evident from the study that the investment decision making in a family is dependent and is associated with the investors’ age, gender, marital status, education, occupation, work experience and life stage on investment decisions. Hence it would be interesting for behavioural study researchers and marketers to know about the investment decisions making in household. Such study helps to design and market financial products and services accordingly for effective segmenting, targeting and positioning (STP). It is concluded that decision making in household is sensitive especially in money matters. In depth study can be done in future since such investment decision making in household may be variable from time to time. 3. Lalit Mohan Kathuria and KanikaSinghania (2012), “Investment Decision Making: A Gender-Based Study of Private Sector Bank Employees”, The IUP Journal of Behavioral Finance, Vol. IX, No. 56 1, 2012. 4. Mandeep Kaur and Tina Vohra, (2012), “Understanding Individual Investor’s Behavior: A Review of Empirical Evidences” Pacific Business Review International, Vol.2, Issue 6. 5. Mittal M and Vyas R K (2007), “Demographics and Investment Choice among Indian Investors”, The IUP Journal of Behavioral Finance, Vol. 4, No. 4, pp. 51-65. 6. Nava Ashraf, (2009), “Spousal Control and Intra-Household Decision Making: An Experimental Study in the Philippines”, American Economic Review 2009, 99:4, 1245–1277 7. NizamettinBayyurt, VildanKarýsýk, Ali Coskun (2013), “Gender Differences in Investment Preferences”, European Journal of Economic and Political Studies - 6 (1) 8. Ravichandran. K (2008), “A study on Investors Preferences towards various investment avenues in Capital Market with special reference to Derivatives”, Journal of Contemporary Research in Management 9. Singh J and Chander S (2006), “Investors’ Preference for Investment in Mutual Funds: An Empirical Evidence”, The IUP Journal of Behavioral Finance, Vol. 3, No. 1, pp. 55-70. 10. REFERENCE 1. 2. Dinesh Gabhane (2013), “Preferences and significance of demographics on the factors influencing InvestmentDecisions: A Study of Investors in Thane City, Maharashtra”, India, Volume No. 3 (2013), Issue No. 07 (July) Dr. M. Muniraju, Joychen Manuel, (2013), “A Study on Investor’s Perception towards Various Avenues of Investment”, Intercontinental Journal of Finance Resource Research Review, Volume 1, Issue 9, Pp 1422 # MJ SSIM VI(II) & VII (I) 2, 2014 Volume VI / VII, Issue II / I 28 SuGyaan Investigating Mutual Fund Performance Persistence *Parag Rijwani ABSTRACT The performance of the mutual funds depends on the successive effort fund manager to time the market. The objective of this study is to examine whether the past performance of the mutual fund reflects the present and future performance of the fund in equity diversified growth funds in India for time 2010-2012. For this study, 188 mutual funds have been observed that exist in the market for the same time period. The assessment of the persistence in performance in the short-run is done based on three major empirical tests: contingency table analysis of winners and losers, chi-squared independence testing on these tables and Ordinary Least Square (OLS) regression analysis of returns. If past performance is a predictor of future performance, first half ‘superior’ funds in the first period would remain as ‘superior’ funds in the next period, second half ‘inferior’ funds in the second half and so on. It is found that returns exhibit strong evidence of persistence in the selected time period. Funds that performed poorly during a prior year are likely to continue their poor performance during the next year and likewise a superior performing fund is likely to continue to perform well during the next year. Key Words: Mutual Funds Performance, Persistence of Returns, Diversified Equity Funds JEL Classification Code : G24 1. Introduction Mutual funds industry has shown a consistent growth over a time period in Indian financial market. The performance of the mutual funds depends on the market timing ability of the fund manager and many of the AMCs boast of their superior performance to attract new investors. All mutual funds advertisements in media contains a disclaimer that the performance data featured represents the past performance which does not assure the future performance of the fund. And still all mutual funds boast of their past performance in the advertisements. Many economists and investors believe that the funds are expected to repeat their performance in the next years. Fund performance is said to be persistent if, for the consecutive time periods, the fund return is above or below the median of all funds after being above or below the median in the previous period. The performance persistence is very important for the individual investors while selecting the mutual funds. As if the persistence exists, then the funds which performed poorly during the past year are likely to perform poorly in the next year also. Similarly, well performing funds are likely to perform better again. It is being one of the most popular topics in mutual funds literature in previous decades because of the huge market of mutual funds in US. The persistence studies has focused on the issue of predicting future performance by using past performance records. The persistence studies is central from the viewpoint of the entire performance measurement as if the past performance has no prediction power over the future performance, the data collecting and expost performance evaluation will be useless procedure from the investor’s view. Investors rely on managers past risk adjusted performance in order to assess their ability to generate excess returns. It is then important to evaluate whether or not past performance has predictive value for future performance. From the market efficiency perspective, the existence of persistent performance conflicts with the efficient market hypothesis. This study is an effort to analyse the performance persistence of the mutual funds in India. 2. Literature Review The earliest work on persistence of mutual funds’ performance is paper by(Sharpe, 1966). The issues raised in this paper include the * Assistant Professor, Institute of Management, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad – 382 481, Email: [email protected], [email protected], M +91 9898002772 Volume VI / VII, Issue II / I SuGyaan performance measure that has to be; considered while measuring the performance of the funds. The previous measure that had been used was Treynor’s ratio which is the ratio of return in excess of risk-free rate to CAPM (Capital Asset Pricing Model) beta of the portfolio. But Sharpe proposed that this approach do not carry firmspecific risk and best only for well-diversified portfolio. So, he recommends his own measure known as Sharpe Ratio (or, reward to variability ratio), which is the ratio of expected excess return of a portfolio to its total risk. Using this measure for 34 mutual funds for previous 20 years period, Sharpe finds positive though not statistically significant correlation. The results from the Treynor’s ratio were also the same. This study was followed by (Jensen, 1968) who used the same length of holding period and selection as Sharpe, but the difference was in the measurement of the performance. In his study, he used Jenson’s alpha for mutual fund performance. He found positive correlation in performance between selection period and holding period indicating the funds can be consistently superior and inferior in the performance. But Jenson also mentioned that this persistence is more sound in case of the funds which had performed inferior in the past. So, the funds which had performed superior not necessarily perform superior again in the next period. The study of Carlson (1970) based on 57 mutual funds with sample data for 20 years (1948-1967) finds that the inter decade rankings based on Sharpe ratio show no persistence but the rankings based on volatility does. So, he came out with the conclusion that the objective of the investment can influence the performance persistence. He again tested 33 common stock funds on the same criteria and found no differences in the results. Carlson again divided each decade into five year period and based on the Sharpe ratio, he found that the funds had the tendency to remain either in the top or the bottom quartiles (groupings). Sarnat(1972) examined the performance of 56 mutual funds with the data for 12 years for both the holding period and selection period. The performance was based on the General efficiency, 29 Risk aversion, Mean-Variance and two stage criterion and efficient sets were formed for examination. The findings said that the composition of efficient sets over time was not stable enough to benefit an investor, or can be said that the performance persistence was found to be weak in the study. Lehmann and Modest (1987) examined the persistence of fund rankings based on the various performance measures (Treynor& Black appraisal ratios, alpha based on the CAPM model, APT model and total returns) for the 15 year period sub-divided into three 5-year periods. The study is considered as a milestone for the performance persistence measurement as it for the first time used multifactor models for the performance measurement. Though the performance persistence was found but the authors also found that this also depend upon the performance measure used. The results showed significant difference between rankings based on CAPM model and APT model. So, Lehman and Modest also stressed on the need of finding the benchmark performance measure to represent the factors determining fund returns. Levy & Lerman(1988) also conducted the study to work out the predictive power of the investments decisions also using information about the riskless assets. The study used the data for the period of 11 years and the result indicated that the results are persistent when selection of efficient sets is based on mean-variance criterion with riskless asset, or the second degree or third degree stochastic dominance criterion with riskless asset. The persistence studies conducted in 1990s showed a shift of research design in terms of the shortening of the selection period and holding period of the data as compared to the earlier studies that used the data generally for the longer period. (Grinblatt & Titman, 1992) examined the performance persistence of mutual funds over the time period of 9 years using methodology based on the eight-portfolio benchmark (P8). The study showed the positive performance persistence and this persistence cannot be explained by the inefficiencies in the benchmark that are related to firm size, dividend yield, past returns, Volume VI / VII, Issue II / I SuGyaan skewness, interest rates sensitivity and CAPM beta. The findings were consistent with the differences in fees and transaction costs across funds also remain persistent. In another study, (Grinblatt & Titman, 1993) developed a new performance measure named Portfolio Change Measure that was used to evaluate the performance on the basis of changes in quarterly portfolio holdings of 155 funds for 10 year time period. The result showed the strong evidence of persistence for the entire sample and weaker evidence for the subsamples of the growth, aggressive growth and growth-income funds. In a US based study, (Hendricks, Patel, & Zeckhauser, 1993) found that in the period 1974– 1988 relative performance of no-load, growthoriented mutual funds persisted in the near term, with the strongest evidence for a one-year evaluation horizon. A study (Coggin, Fabozzi, & Rahman, 1993) examined the investment performance of US equity pension fund managers. They found that pension fund managers were good at picking stocks, but poor at timing the market. The best managers produced substantial risk-adjusted excess returns. The relative riskadjusted performance persistence was found in a study; however, the persistence was mostly due to funds that lag the S&P 500, depends upon the time period observed and is correlated across managers (Brown & Goetzmann, 1995). Bond funds underperformed the returns predicted by a relative pricing model that they developed by the amount of expenses, on average (Elton, Gruber, & Blake, 1995). They note that there is no evidence that managers, on average, can provide superior returns on the portfolios they manage, even if they provide their services free of cost. Grinblatt, Titman and Wermers(1995) found that mutual funds which bought past winners (followed a momentum strategy) realized significantly better performance than other funds. Brown, Harlow and Starks (1996) looked at growth-oriented mutual funds and demonstrated that mid-year losers tend to increase fund volatility in the latter part of an annual assessment period to a greater extent than mid-year winners. 30 Elton, Gruber and Blake (1996a) provide estimates of survivorship bias that can be used as benchmarks to determine the amount of bias in studies that do not take survivorship bias into account. Elton, Gruber and Blake (1996b) found persistence in risk-adjusted stock mutual fund returns. Ferson and Schadt(1996) advocate conditional mutual fund performance evaluation in which the relevant expectations are conditioned on public information variables. This method made the average performance of the mutual funds in their sample look better. Gruber (1996) seeks to solve the puzzle as to why investors buy actively managed open end mutual funds when their performance on average has been inferior to that of index funds. He suggests that the solution to the puzzle is that if managers have skill, future performance is in part predictable from past performance, and this management ability may not be included in the price. Ferson and Warther(1996) modified classical performance measures to take account of well-known market indicators (interest rates, dividend yields and other commonly available variables). This conditional performance evaluation makes mutual funds’ performance look better. Goetzmann and Peles(1997) presented evidence that cognitive dissonance explains mutual fund investor inertia. That is, investor aversion to switching from poor performers may be explained by overly optimistic perceptions of past mutual fund performance. Carhart(1997) considered the persistence in equity mutual funds’ mean and risk-adjusted returns. He concluded that the results do not support the existence of skilled or informed mutual fund portfolio managers. Daniel, et al. (1997) looked at the performance of equity mutual funds. Their results showed that mutual funds, particularly aggressive-growth funds, exhibit some selectivity ability, but that funds exhibit no characteristic timing ability. Indro, et al. (1999) reported that fund size (net assets under management) affects mutual fund performance and found that, in effect, 20% of nonindexed US equity funds were too small and 10% too large. Ackermann, McEnally and Ravenscraft(1999) examined hedge fund data Volume VI / VII, Issue II / I 31 SuGyaan from 1988–1995 and found that hedge funds consistently outperform mutual funds, but not standard market indices. However, hedge funds are more volatile than both mutual funds and market indices. Incentive fees explained some of the higher performance, but were not correlated with total risk. Chevalier and Ellison (1999) found that mutual fund managers who attended higher-SAT undergraduate institutions have systematically higher risk-adjusted excess returns. Liang (1999) looked at hedge fund performance. “Funds with “high watermarks” (under which managers are required to make up previous losses before receiving any incentive fees) significantly outperform those without. Hedge funds provide higher Sharpe ratios than mutual funds, and their performance in the period of January 1992 through December 1996 reflects better manager skills, although hedge fund returns are more volatile. Average hedge fund returns are related positively to incentive fees, fund assets, and the lockup period.” Edelen(1999) show that the common finding of negative return performance at open-end mutual funds is attributable to the costs of liquidity motivated trading: open-end equity funds provide diversified equity positions with little direct cost to investors for liquidity. Blake, Lehmann and Timmermann(1999)analysed a data set on UK pension funds. Their main finding was that strategic asset allocation accounts for most of the ex post variation of UK pension funds’ returns. Moreover, the vast majority of funds had negative market-timing estimates. Wermers(2000) examined mutual fund databases and concluded that their evidence supported the value of active mutual fund management. Liang (1999) studied hedge fund performance and risk from 1990 to mid- 1999. Hedge funds had an annual return of 14.2 percent in this period, compared with 18.8 percent for the S&P 500 Index, although the S&P 500 was much more volatile. Kothari and Warner (2001) argue that standard mutual fund performance measures are inadequate for detecting abnormal fund performance. They suggest using event-study procedures that analyse a fund’s stock trades. Berk and Green (2004) derived a parsimonious rational model of active portfolio management. They state that “the lack of persistence in returns does not imply that differential ability across managers is non-existent or unrewarded or that gathering information about performance is socially wasteful.” Bollen and Busse(2005) examine daily mutual fund data, consider quarterly returns and conclude that superior performance is a short-lived phenomenon that is observable only when funds are evaluated several times a year. Droms and Walker (2006)analysed fixed income mutual fund performance persistence for government and corporate bond funds. According to this study, the government and corporate bond funds exhibit remarkable performance persistence as z-statistics for these are statistically significant. It showed that if intermediate-term (long-term) bond returns are higher than long-term (intermediate-term) bond returns for successive years, then the z-statistics is positive (or, say that persistence is positive). By contrast, if higher returns on intermediate (long) bonds are followed by a year of higher returns on long (intermediate) binds, then persistence is negative. Also, they suggest that the nature of persistence (i.e. normal vs. perverse persistence) is driven by changes in interest rates. As the changes in the interest rates cause market leadership to change from on bond to another (i.e. higher returns to intermediate or long term bonds), the nature of persistence changes. So, the stability of market leadership is associated with the positive persistence. Similarly a study (Fortin & Michelson, 2010) examines the performance persistence of a large sample of equity and bond fund categories over the time period of ten years and found significant performance persistence in mutual fund returns for all categories except government bond and corporate bond funds. The outcome tends to be true for both highest performing as well as lowest performing funds but do not applies to the funds in the middle performance categories. 3. Research Problem The literature appears to support performance persistence in the past, but the results are mixed. Volume VI / VII, Issue II / I 32 SuGyaan Also, the studies done in this area are majority in the developed countries like US, UK etc. This study is intended to extend the previous research in the Indian Mutual Fund industry. Thus, the question that it addresses is; does the performance persistence exist in mutual funds in India? 4. Research Objectives To study the presence of performance persistence of equity diversified- growth mutual funds in India. 5. Methodology Research Hypothesis: The research will test the hypothesis that diversified mutual funds show significant performance persistence over the study period. H0: The performance persistence does not exist in the equity diversified- growth mutual funds in India. H1: The performance persistence exists in the equity diversified- growth mutual funds in India. Data Source: Secondary data that is collected from ACE Equity database of Accord Fintech Pvt. Ltd. and websites like Value research online, AMFI. Scope: Equity diversified open ended regular funds in India that are the survivor for the studied time period. Sampling Population:The mutual fund industry in India is consisting of more than forty four Asset management Companies (AMC). There are 202 mutual funds scheme in Equity-diversified growth option as on December 2012 (as per SEBI data). Unit:The unit is being the one equity diversifiedgrowth mutual fund scheme. Size:The sample size is 188 mutual funds with data for the previous 3 years which is divided into sub-period of 3 months each. Technique:The judgmental sampling is used to select the sample where the criterion for selection is the schemes with at least 3 years in operation. from December 2009 through June 2014. Though there were total 202 mutual funds were operating for the same time period but the data for few mutual funds was not available, so number decreased to 188. The data set consists of quarterly NAVs data for these funds from the ACE MF database. Returns are calculated as the percentage total rate of return for the fund. Table 1 provides the general characteristics of the dataset for the different time periods. Data Analysis: First contingency tables are used to analyse performance persistence. For contingency analysis, the funds are categorized as a “winner” or “loser” in each time period. Winner/Loser (W/L) is determined by comparing each fund’s return to the median return for that funds category (In this case equity diversified funds). If a fund’s return is greater than or equal to the median, it is classified as a Winner. Funds lower than the median are classified as a Loser. On a time period and overall basis the funds are tabulated as Winner/Winner, Winner/Loser, Loser/ Winner, and Loser/Loser. The fund return are calculated using the raw Net Asset Value (NAV) as follows: Returnt= ∆NAVt/ NAVt-1 Cross-Product Ratio reports the odds ratio of the number of repeat performers to the number of those that do not repeat; that is, {WW*LL)/ (WL*LW). The null hypothesis that performance in the first period is unrelated to performance in the second period corresponds to an odds ratio of one. In large samples with independent observations, the standard error of the natural log of the odds ratio is well approximated. Using the Odds-Ratio the Z-statistic and accompanying P-value is computed. Additionally the nonparametric Chi-Square statistic is calculated to determine the P-value as well. The odds ratio (OR), its standard error and 95% confidence interval are calculated as under (Altman, 1991) The odds ratio is given by Data:Quarterly mutual fund data are collected for a total of 188 equity diversified mutual funds those are in operation during the 3-year period Volume VI / VII, Issue II / I 33 SuGyaan with the standard error of the log odds ratio being heteroscedasticity-consistent variance-covariance matrix. The adjusted i-statistic is calculated as follows: t-statistic = Coefficient/ HSCE and 95% confidence interval Where zeros cause problems with computation of the odds ratio or its standard error, 0.5 is added to all cells (a, b, c, d) To analyse statistical significance, following statistics are used: And, χ2 = Σ(Oi – Ei)2/Ei Where O, is the observed number in each bin and Ei is the expected number in each bin. Π2 follows a chi-square distribution with 1 degree of freedom in the case of a two-by-two table and (R -l)*(C- 1) degrees of freedom in an R by C contingency matrix. Another methodology that is used for first investigation of persistence is OLS regression analysis, regressing Period 2 performance against Period 1 performance. Performance (2) = a + b*Performance (1) + e Where, “performance” can be cumulative total returns, cumulative selection returns, orinformation ratios. Positive estimates of the coefficient b with significant t-statistics are evidence of persistence or Period 1 performance contains useful information for predicting Period 2 performance. In this case the raw returns have been taken as the measurement of the performance. Henriksson(1984) and Merton (1981) suggest the managed portfolio’s return will exhibit conditional heteroscedasticity because of the fund manager’s attempt to time the market, even when stock returns are independently and identically distributed through time. Breen, Jagannathan, and Ofer(1986) show the importance of correcting for heteroscedasticity in return studies and document the adequacy of White’s (1980) correction. We use White’s whereHSCE is the heteroscedastic-consistent standard errors. This regression technique is being used as the verification technique for the first used contingency table and odd-ratio results. 6. Empirical Results Contingency Table and Odd-ratio Results In table 2, the two-way contingency table shows the numbers of funds that were winners in both periods, losers in periods, winners then losers, and losers then winners. The combined results of all eleven periods can be seen in the table 3. From Table 2, it can be seen that the numbers of funds in the diagonal bins (top left and bottom right) are relatively higher, providing evidence of persistence in each quarter interval period. However, this evidence of persistence is not very strong for the Q2 2010-Q3 2010 period, Q3 2010Q4 2010, Q3 2012-Q4 2012 and Q1 2013- Q2 2014 period which is confirmed by the chi-squared test with insignificant statistics of 1.36, 0.34, 1.36 and 0.34 respectively. This implies that the performances in these quarters are independent of the previous quarter performances. And the statistics of the remaining time periods are statistically significant exhibiting the strong evidence of the performance persistence in sample. In table 4, the significance of persistence of returns is tested by calculation of a z-statistic, which is distributed normally with a zero mean and a standard deviation of 1.0. A large positive zstatistic is obtained when a high percentage of the “winners” in one period remain “winners” in the next period tested. When a high percentage of “winners” in one period become “losers” in the next period, a large negative z-statistic is found. Small z-statistics are determined when there is no clear pattern in the returns. If exactly the same winners remain winners and the same losers remain losers between two periods, the z-statistic would be zero. Statistics are judged at the fiveVolume VI / VII, Issue II / I 34 SuGyaan percent level of significance. Same as chi-square test, the z-statistic is not statistically significant for the four time periods, time period 2, 7, 11 and 13. Also, it can be seen that the z-statistic come to be negative when the number of winners ought to become the losers in the next time period. The combined z-statistic is statistically significant indicating that the one time period performance affects the next time period performance of the mutual fund. So, the significant values of the zstatistics states that the hypothesis of no performance persistence can be rejected in most of the cases (13 out of 17 time periods). Based on the results of the above two tests it can be concluded that the performance persistence exists among the equity diversified-growth mutual funds. Regression Results Table 5 consists of the results of the regression done on the returns as the time period 1 performance as an independent variable and time period 2 performance as a dependent variable. All values of t-statistics have been adjusted with White’s correction to remove the heteroscedasticity in returns. The slope for the most of the time periods comes to be positive and the t-statistics are also significant for the most of the time periods exhibiting strong evidence of the performance persistence. Also, the results are consistent with both of the parametric tests (Chi-square and oddratio) as the t-statistics for the same time periods are not significant enough to show the performance persistence. Only, in one case (time period 9) there is a contradictory result when the regression shows no performance persistence and non-parametric tests show the performance persistence. So, out of the 17 time periods, the regression results show that in 12 such periods, there is the existence of the performance persistence. 7. Findings The evidence for persistence of equity diversified growth fund performance is found. What are the investment implications of these results? For equity funds, the implications are simple. With persistence of selection returns, unless one have another basis for choosing future winners (i.e., one’s selection criteria include information other than historical performance), the solution is to rank the performance to match ones investment objectives. Since there is evidence of persistence in our study, this may suggest that there are two types of investors in the market. The first type being the ‘superior’ investors (that is, investors with superior information) while the latter type being known as the ‘momentum’ investors (one who buys past ‘winners’ and sells past ‘losers’) as suggested by Grinblatt and Titman (1989) and (1993)andGrinblatt, Titman and Wermers(1995)respectively. It is said that both types of investors contribute to the positive performance of mutual funds. 8. Conclusions This study presents the results of an analysis of equity diversified-growth mutual fund performance. The study applies the “winnerwinner, winner-loser” methodology as well as OLS regression methodology to test for short-term performance persistence in mutual funds from January 2010 to June 2014 with analysis done on the quarterly basis. We use the non-parametric Odds-Ratio and Chi-Square tests to examine significance in performance persistence for the first methodology. Similarly, the regression results are adjusted for the heteroscedasticity because of the time-series data using White heteroscedasticity variance matrix. We found that there is significant performance persistence in mutual fund returns. This outcome is true for both the lowest performing and highest performing mutual funds. Investors of mutual funds face two important decisions viz. selecting and mutual fund scheme for investments and reviewing the performance of the existing mutual funds schemes. Both these decisions involve a careful dissection of attributes of the mutual fund scheme. Past return is one of the important variable used in fund selection and evaluating the performance of the fund as a part of review. The question is, do past returns matter? Does it make any sense to choose a mutual fund that has performed consistently in the past? After all, there is no guarantee that it would continue to perform well in future. The disclaimer of ‘past Volume VI / VII, Issue II / I 35 SuGyaan performance is not indicative of future’ is valid. However, the empirical results here suggest that past performance persist in future. The results of this study are important to individual investors when selecting mutual funds. Investors should be cognizant of previous returns for any funds under consideration. If a fund performed poorly during the past year, it is likely the fund will continue to perform poorly in the next year. Likewise if a fund performed well during the past year, it is likely the fund will perform well during the next year. Note that persistence appears to exist for the best and worst performing fund categories. Therefore, an investor selecting funds in the middle performance categories is not likely to see the same persistence in returns. As a caveat we understand that there is survivorship bias when performing mutual fund research. A fund must have survived across the study period are included, so funds that underperformed and were subsequently closed to investors are not included in this study. Some past researchers have considered this dropping of samples as bias against finding significant performance persistence for the worst performing quintile of funds. References: 1. Ackermann, C., Mcenally , R., & Ravenscraft, D. (1999). The performance of hedge funds: Risk, return, and incentives. The Journal of Finance, 54(3), 833–874. 2. Altman. (1991). Practical statistics for medical research. London: London: Chapman and Hall. 3. 4. 5. Berk , J. B., & Green, R. C. (2004). Mutual fund flows and performance in rational markets. Journal of Political Economy, 112(6), 1269– 1295. Blake, D., Lenmann, B. N., & Timmermann, A. (1999). Asset allocation dynamics and pension fund performance. The Journal of Business, 72(4), 429–461. Bollen, N. P., & Busse, J. A. (2005). Short-term persistence in mutual fund performance. Review of Financial Studies, 18(2), 569–597. 6. Breen, W., Jagannathan, R., & Ofer, A. (1986). Correcting for Heterscedasticity in Tests for Market Timing Ability. Journal of Business, 59, 585-598. 7. Brown, K. C., Harlow, W. V., & Starks, L. T. (1996). Of tournaments and temptations: An analysis of managerial incentives in the mutual fund industry. The Journal of Finance, 51(1), 85–110. 8. Brown, S. J., & Goetzmann, W. N. (1995). Performance Persistence. Journal of Finance, 50(2), 679–698. 9. Carhart, M. (1997). On persistence in mutual fund performance. The Journal of Finance, 52(1), 57–82. 10. Carlson, R. S. (1970). Aggregate Performance of Mutual Funds 1948 1967. Journal of Financial and Quantitative Analysis, 5, 1-32. 11. Chevalier, J., & Ellison, G. (1999). Are some mutual fund managers better than others? Cross-sectional patterns in behaviour and performance. . The Journal of Finance, 54(3), 875–899. 12. Coggin, D. T., Fabozzi, F. J., & Rahman, S. (1993). The Investment Performance of U.S. Equity Pension Fund Managers: An Empirical Investigation. The Journal of Finance, 43(3), 1039–1055. 13. Daniel, K., Grinblatt, M., Titman, S., & Wermers, R. (1997). Measuring mutual fund performance with characteristic-based benchmarks. The Journal of Finance, 52(3), 1035–1058. 14. Dromos, W., & Walker, D. A. (2006). Performance Persistence of Fixed Income Mutual Funds. Journal of Economics and Finance, 30(3), 347-356. 15. Edelen, R. M. (1999). Investor flows and the assessed performance of open-end mutual funds. Journal of Financial Economics, 53(3), 439–466. 16. Elton, E. J., Gruber, M. J., & Blake, C. R. (1995). Fundamental economic variables, expected returns, and bond fund performance. The Journal of Finance, 50(4), 1229–1256. 17. Elton, E. J., Gruber, M. J., & Blake, C. R. (1996a). Survivorship bias and mutual fund Volume VI / VII, Issue II / I SuGyaan 36 performance. . The Review of Financial Studies, 9(4), 1097–1120. Investigation. Journal of Business, 57(1), 7396. 18. Elton, E. J., Gruber, M. J., & Blake, C. R. (1996b). The persistence of risk-adjusted mutual fund performance. . The Journal of Business, 62(2), 133–157. 30. Indro, D. C., Jiang, D. C., & Lee, W. Y. (1999). Mutual fund performance: Does fund size matter? Financial Analysts Journal, 55(3), 74– 87. 19. Ferson, W. E., & Warthe, V. A. (1996). Evaluating fund performance in a dynamic market. Financial Analysts Journal, 52(6), 20– 28. 31. Jensen, M. (1968). The Performance of Mutual Funds in the period 1945-1964. Journal of Finance, 23, 389-416. 20. Ferson, W. E., & Warther, V. A. (1996). Measuring fund strategy and performance in changing economic conditions. . The Journal of Finance, 51(2), 425–461. 21. Fortin, R., & Michelson, S. (2010). Mutual Fund Performance Persistence: Still True? Academy of Accounting and Financial Studies Journal, 14, 29-41. 22. Goetzmann, W. M., & Peles, N. (1997). Cognitive dissonance and mutual fund investors. Journal of Financial Research, 20(2), 145–158. 23. Grinblatt, M., & Titman, S. (1989). Mutual Fund Performance: An Analysis of Quarterly Portfolio Holdings. Journal of Business, 62(3), 393-416. 24. Grinblatt, M., & Titman, S. (1992). The Persistence of Mutual Fund Performance. Journal of Finance, 47(5), 1977-1984. 25. Grinblatt, M., & Titman, S. (1993). Performance Measurement without Benchmarks: an Examination of Mutual Fund Returns. Journal of Business, 66, 47-68. 26. Grinblatt, M., Titman, S., & Wermers, R. (1995). Momentum investment strategies, portfolio performance, and herding: A study of mutual fund behavior. . The American Economic Review, 85(5), 1088–1105. 32. Kothari, S. P., & Green, R. C. (2001). Evaluating mutual fund performance. The Journal of Finance, 56(5), 1985–2010. 33. Lehmann, B. N., & Modest, D. M. (1987). Mutual Fund Performance Evaluation: A Comparison of Benchmarks and Benchmark Comparisons. . Journal of Finance, 42(2), 233265. 34. Levy, H., & Lerman, Z. (1988). Testing the Predictive Power of Ex Post Efficient Portfolios. Journal of Financial Research, 11(3), 241-254. 35. Liang, B. (1999). On the performance of hedge funds. Financial Analysts Journal, 55(4), 72– 85. 36. Liang, B. (1999). On the performance of hedge funds. . Financial Analysts Journal, 55(4), 72– 85. 37. Merton, R. (1981). On Market Timing and Mutual Fund Performance II: Statistical Procedures for Evaluating Forecasting Skills. Journal of Business, 54(4), 513-533. 38. Sarnat, M. (1972). A Note on the Prediction of Portfolio Performance from Ex Post Data. Journal of Finance, 903-906. 39. Sharpe, W. (1966). Mutual Fund Performance. Journal of Business, 119-138. 27. Gruber, M. (1996). Another puzzle: The growth in actively managed mutual funds. The Journal of Finance, 51(3), 783–810. 40. Wermers, R. (2000). Mutual fund performance: An empirical decomposition into stock-picking talent, style, transactions costs, and expenses. The Journal of Finance, 55(4), 1655–1695. 28. Hendricks, D., Patel, J., & Zeckhauser, R. (1993). Hot Hands in Mutual Funds: Shortrun Persistence of Relative Performance. Journal of Finance, 48(1), 93-130. 41. White, H. (1980). A HeteroscedasticityConsistent Covariance Matrix Estimator and a Direct Test for Heteroscedasticity. Econometrica, 48, 817-838. 29. Heriksson, R. (1984). Market Timing and Mutual Fund Performance: An Empirical # MJ SSIM VI(II) & VII (I) 3, 2014 Volume VI / VII, Issue II / I SuGyaan 37 Volume VI / VII, Issue II / I SuGyaan 38 Volume VI / VII, Issue II / I SuGyaan 39 Volume VI / VII, Issue II / I SuGyaan 40 Volume VI / VII, Issue II / I SuGyaan 41 Volume VI / VII, Issue II / I 42 SuGyaan PRELIMINARY PERFORMANCE ANALYSIS OF S&P BSE 500 SHARIAH INDEX Pardhasaradhi Madasu* ABSTRACT This study is motivated by the impressive growth of Islamic Finance Industry. Islamic investments follow the Shariah guidelines. Shariah is the Muslim law which regulates many aspects of a Muslim’s life including the type of investments allowed. The concept of Shariah has brought in major changes in the finance and investment world. In one way a new sub-segment named ‘Islamic Finance Industry’ has taken shape. Islamic finance industry has undergone a transformation in the last few years. Today it has started asserting itself as an alternate system of finance. Diverse Shariah compliant financial products, which include banking products like savings and current accounts (based on Wadia and Qard), (Mudarabah based) investment accounts, financing products such as Home financing and Ijarah, insurance products and capital market products like Mutual Funds, Portfolio Management Services and Stock broking, are being offered in both Muslim and secular countries. Shariah prohibits investments in companies which indulge in business activities prohibited by Shariah. So, Shariah compliant stocks are those stocks whose income is not derived from prohibited activities. Stocks are screened for Shariah compliance by using certain Shariah screening norms. “Taqwaa Advisory and Shariah Investment Solutions (TASIS) Pvt. Ltd” is the leading Shariah advisory institution in India; it has formulated norms for Shariah screening of Indian stocks, which are widely acknowledged and accepted in the country. Following the popularity of Shariah investments the investors were looking for a benchmark index that could be used for comparing the returns on the Shariah compliant stocks. In 2006, S & P Dow Jones Indices introduced the S & P Shariah Indices. On Feb 19, 2013, S & P Dow Jones Indices and the Bombay Stock Exchange have created S & P BSE 500 Shariah Index. This index was designed to represent all Shariah compliant stocks of the broad based S & P BSE 500 Index. The present paper is an attempt to analyze the performance of the Indian Shariah Index. Key Words: Islamic Finance, Shariah Compliant Stocks, and Shariah Index. JEL Classification Code : G10 1.0 Introduction Islamic finance industry has undergone a transformation in the last few years. Today it has started asserting itself as an alternate system of finance. This industry has made a mark by its rapid growth not only in Muslim countries but also in other secular and developed nations as well. As per the Report of PriceWaterCoopers in 2009 Muslims represent 25% of the World’s Population, but less than 1% of global financial assets are Shariah compliant1. It is believed that a growing Muslim population base, with wealth geographically concentrated in the Middle East, is underserved by the current Islamic Financial Service providers. Further, the E & Y Report in 2010 states that the market for Islamic products is growing 15 – 20% per year. The reason for low participation by Muslim investors can be traced to strict dictates of The Shariah. As per the ShariahMuslim investors should ensure the income they earn adheres to the guidelines of The Shariah2. Their earnings should be pure and choice. The Shariah guidelines prohibit financial involvement with companies such as conventional banks, casinos and alcohol producers. Another key element of Islamic investing is the avoidance of interest, or Riba. All these strict guidelines make it difficult to Investors who have faith in Islam to invest in companies because they cannot screen these companies on individual basis. Initially, to choose Shariah compliant investments the investors used to approach investment advisors and these advisors used to suggest the investment avenues. In short, the investors who had strong faith Islam were investing based on the Shariah Investment Solution provided by the advisors. However, over a period of time there was a change in the perception of the regulators and leaders of *Associate Professor, Siva Sivani Institute of Management, Kompalli, Secunderabad, Mobile – 07799207014; e-mail : [email protected] Volume VI / VII, Issue II / I 43 SuGyaan financial markets and a need was felt for tapping these untapped markets by introducing the Shariah compliant financial products 3 that adheres to Shariah guidelines. Shariah prohibits investments in companies which indulge in business activities prohibited by Shariah. So, Shariah compliant stocks are those stocks whose income is not derived from prohibited activities. Stocks are screened for Shariah compliance by using certain Shariah screening norms. There are two steps involved in Shariah screening of stocks, Firstly, screening on the basis of activity and secondly, financial screening. Stocks or companies which pass both the criteria are known as Shariah compliant stocks or companies. There are several Shariah screening institutions which have formulated their own Shariah screening norms under the guidance of their respective Shariah Boards. The better known screening norms in use around the world are those of AAOIFI, Dow Jones, MSCI, S&P and TASIS. In the first step of the screening process, companies which are involved in prohibited business activities are screened out4. The companies which pass the business screening test are termed as “Business compliant” and they are put through financial screening by further applying the financial norms 5 . The business compliant companies or stocks which qualify on the three financial screening criteria are termed as Shariah compliant companies. Investment in such Shariah compliant stocks is called Shariah compliant investment. Financial institutions like Mutual Funds, Insurance, Portfolio management services, etc. are using these Shariah compliant stocks to build profitable Shariah compliant investment portfolios and offer Shariah compliant investment products to Shariah conscious investors. Out of the available investment vehicles the preferred Islamic investment format is ‘Equity’6. The reason for the ‘Equity’ to be preferred for Shariah investment is that ownership comes along with equity and equities do not confer any assured benefits on the holder7. In fact the shareholder could even stand to lose his entire capital in the event the company in which he has invested suffers massive losses. Nor does equity investment necessarily involve the element of randomness and uncertainty associated with gambling and games of chance. The rights and obligations of the parties too are clearly defined and do not involve exploitation or injustice. Because of the importance of ‘Equities’ in the Shariah investment many stock exchanges have started constructing and publishing ‘Equity Indices’ based on Shariah compliant companies. Shariah-compliant indices were introduced by globally reliable indices’ providers including Dow Jones, FTSE, Standard & Poor’s and Morgan Stanley. All Islamic indices follow a common stock selection process which is termed as stock screening. While basic prohibitions and Shariah rules are strictly maintained in the screening process, different indices may differ in some screening criteria. The benchmarks from which Islamic indices are selected are well-recognized conventional indices. In this background, the present paper has the following objectives of study: 1. To understand the conceptual framework of Shariah Compliant Indices 2. To conduct wide review of literature relating to the performance analysis of Islamic Equity Indices 3. To study the performance of S & P BSE SHARIAH INDEX 4. To conduct a comparative analysis of BSE Sensex and BSE Shariah Index 2.0 Literature Review Many of the studies that have dealt with Islamic investment or Shariah investment had brought in the dimension of ethical investment. The literature related to social responsible investing and also ethical investing are both relevant to the present study. The present study being dedicated on the performance analysis of Shariah Index or Islamic Index has focused on the literature relating to the performance analysis of Islamic Index or ethical funds. Majority of these studies followed the same methodologies of comparing the performance of DJIMI to other benchmarks but the choices are quite different from one research to another in terms of performance measures and benchmarks. Some of the studies have analyzed the performance of the FTSE Islamic indices. Volume VI / VII, Issue II / I SuGyaan The initial studies relating to comparative performance of ethical and non-ethical funds in the UK were conducted in 1995 by Mallin, Saadouni, and Briston. They have stated that ethical and non-ethical funds were not able outperform the overall market but they have found that ethical funds performed better than non-ethical funds. The measurements used for the analysis were traditional risk-adjusted measurements such as the Jensen alpha, the Sharpe ratio, and the Treynor ratio. Among the studies that are focused on the Islamic Equity Indices the study conducted by Atta (2000) may be referred as the earlier study. The study used the Dow Jones Market Index (DJIMI) for understanding the performance of Islamic equity indices. The present study being performance analysis of BSE Shariah Index draw much of its motivation form study conducted by Ahmad and Ibrahim (2002) which compared the performance of Malaysia Stock Indices such as KLSI with that of KLCI over the period from 1999 to 2002. They used various methodologies to investigate the performance, measured by the risk and return of both indexes. Among the techniques used were the adjusted Sharpe ratio (SR), the Treynor Index (TI), the adjusted Jensen Alpha, and the t-test for comparing the means. They divided the sample into three periods: the overall sample, the period of growth from April 1999 to February 2000 and the period of decline from March 2000 to January 2002. In comparing the raw returns and risks during 1999–2002, they concluded that for the overall and the declining periods, the return was low for KLSI, while for the growing period the KLSI slightly outperformed the KLCI. In terms of risk, the KLCI was riskier than the KLSI over 1999–2002. When comparing the means, the results were statistically insignificant. In addition, the KLSI reported lower risk-adjusted returns than the KLCI, except during the growing period 1999– 2000. Study conducted by Hakim and Rashidian (2002) has examined the risk and returns of Islamic stock market index in US by using cointegration analysis and causality analysis to investigate the 44 relationships among the Dow Jones Islamic Market Index (DJIMI), the broad stock market represented by the Wilshire 5000 Index, and the risk-free rate proxies by 3-m T-bill, but found no visible link among them. The results showed that the Islamic index was influenced by factors independent from the broad market or interest rate. In one way the study has differed from the claim of Dow Jones Inc. that the index exhibits significant high correlation with the broad market. The new evidence suggested that such correlation was merely temporary and spurious. However, their findings suggested that the Islamic index presents unique risk-return characteristics, which are known as company or unsystematic risk and returns, an observation reflected in a risk profile significantly different from the Wilshire 5000 Index. This result is even more important given the fact that the Wilshire 5000 Index is considerably more diversified than the Islamic index. Hussein and Omran (2005) studied the performance of the Islamic index in the Dow Jones against the Dow Jones index from 1995 until 2003 based on monthly data. The sample was divided into three sub-periods: the entire period, the bull period and the bear period. Their results suggested that the Islamic index outperformed the non-Islamic index both in the entire and bull periods, while the opposite is true for the bear period; however, it was not statistically significant in the bear period. Similr study by Elfakhani, Hasan, and Sidani (2005) investigated the performance of the Islamic mutual funds in several emerging countries (including Malaysia). They concluded that there was no statistically significant difference between Islamic and conventional funds. Therefore, the screening mechanism does not affect the performance of Islamic investments. Review of literature indicates that there is no definite proof that the ethically screened or socially responsible or Shariah compliant stocks or funds are outperforming the conventional or traditional stocks or funds. Further, the studies relating to Islamic Equity Indices have also revealed diverse results. Volume VI / VII, Issue II / I 45 SuGyaan 3.0 Data and Methodology The data for the study has been collected from the BSE and S & P Dow Jones Websites. The study being descriptive and exploratory in nature has used fundamental statistical tools such as averages, standard deviation and correlation to analyze the performance of the Index under study. The period of data collection is from 1st Aug, 2009 to 31st July, 2014. In total the closing index values of five indices BSE has been collected – SENSEX, BSE 100, BSE 500, BSE 500 Shariah Index. 4.0 Data Analysis For analyzing the Index the following methodology has been adopted. Table 1 and Figure 1 indicate the sector8 wise composition of the indices. The Shariah Index is composed mostly of companies from Information Technology and Health Care Sector. The combined contribution of both Information Tech. and Health Care Sector in the Shariah Index is 48.3% which is nearly 50 % of the Index weight. On the other hand Sensex, BSE 100 and BSE 500 has given more weightage to Financial Sector and Information Technology. The combined weight of Financial andInformation Tech. Sector in the Sensex, BSE 100 and BSE 500 is equal to 43% approx. The main reason for low weightage for financial services firms in the BSE Shariah Index is that these firms are non-shariah compliant as per the Islamic Law. Table 2 depicts the Market Capitalization across all the premium indices of BSE in comparison with Shariah Index. Table 3 illustrates the comparative risk and return analysis. The ‘Total Return’9 of Shariah Index for all the time periods (viz. 1 yr, 3 yr. and 5 yr) is higher than the benchmark index Sensex. The total return of Shariah index when compared to BSE 100, BSE 200 and BSE 500 for 1 yr period is lower but when the total return for the said indices are compared for 3 and 5 years periods the Shariah index is showing superior performance. The Shariah index is shown superior performance (in all the three periods) over other indices based on basic risk measure ‘Standard Deviation’. Table 4 depicts the correlation between the Shariah index and other BSE Indices. The correlation between these indices is very high (> 0.50)10. 6.0 CONCLUSION The need for creating a conducive environment for socially responsible and ethical investing has been felt from long time. However, in the recent past both emerging economies and the developed economies have started to put regulations in place such that financial products which are attractive to ethical investors are freely available in the financial markets. In this background Shariahcompliant investing has grown considerably in recent decades. The investors who believe in Islamic Law wanted a transparent market mechanism for trading equity and other Shariah Compliant equity products. In this background the stock exchanges have started to partner with popular index service providers to construct and publish indices that are Shariah-Compliant. Analyzing the performance of these variant of indices will be useful for proper portfolio management. References 1. Ahmad, Z., & Ibrahim, H. (2002). A study of the performance of the KLSE Syari’ah index. Malaysian Management Journal, 6(1), 25–34. 2. Elfakhani, S., Hasan, M. K., &Sidani, Y. (2005). Comparative performance of Islamic versus secular mutual funds. Paper presented at the 12th Economic Research Forum, University of New Orleans, US. 3. Hakim, S., &Rashidian, M. (2002). Risk and return of Islamic stock market. Paper presented at the Presentation to Economic Research Forum Annual Meetings, Sharjah, UAE, October 2005 4. Hussein, K. (2005). Islamic investment: Evidence from Dow Jones and FTSE indices. Paper presented at the International Conferences on Islamic Economics and Finance, Indonesia. 5. Hussein, K., &Omran, M. (2005). Ethical investment revisited: Evidence from Dow Jones Islamic Indexes. Journal of Investing, 14(3), 105–124. Volume VI / VII, Issue II / I 46 SuGyaan 6. Iqbal, M. 2002. Islamic Banking and Finance: Current Developments in Theory and Practice. Islamic Foundation, Leicester, UK. (Footnotes) 1 In India, several prominent studies in recent years have found that Muslim participation in the country’s financial system is minimal. The Sachar Committee Report (2006) found that nearly half of India’s Muslim population was excluded from the formal financial sector. The committee among other things observed that the creation of the index will help promote financial inclusion of the Muslims in India and attract investment flows from international funds that must adhere to Shariah norms. 2 Investment in Shariah compliant stocks is not meant only for Muslims; socially responsible investors of any faith could invest in these stocks as, in effect, the process of Shariah screening removes companies deemed to be socially harmful. 3 Diverse Shariah compliant financial products, which include banking products like savings and current accounts (based on Wadia and Qard), (Mudarabah based) investment accounts, financing products such as Home financing and Ijarah, insurance products and capital market products like Mutual Funds, Portfolio Management Services and Stock broking, are being offered in both Muslim and secular countries. 4 The prohibited sectors include interest based financial institutions such as banking, insurance, brokerage financial products and provision of fund based financial services, manufacture, distribution and sale of potable alcoholic beverages and narcotics, processing, distribution and sale of pork and pork related products, meat and products of other animals killed in a nonhalal manner, gambling and tobacco. 5 Norm 1 - Their total interest-bearing debt (including from banks, financial institutions, public deposits and inter-corporate deposits) and issued preference capital should not be greater than 25% of their total assets, Norm 2 - Their interest income from all sources and 8% of interest-based investments should not exceed 3% of their total income, Norm 3 - Their receivables and cash & bank balance should not be greater than 90% of their total assets 6 Preferred Stock and Convertible Stocks are not compliant with the Shariah Investment. On the other hand ETF or ETNSs and REITS are Shariah Compliant. 7 Due to the prohibition of interest, the need for equity markets is higher in Islamic finance (Iqbal 2002). 8 Based on GICS Sectors 9 The Total Return Index is different from the Price Return Index. A Price Index considers only the capital gains viz. changes in prices over a period of time. The Total Return Index (TR) measures the performance by assuming that all cash dividends are reinvested. 10 Islamic indices are subsets of conventional benchmarks that include only those companies passing rules-based screens for Shariahcompliance. The resulting Shariah indices tend to be highly correlated to their conventional counterparts and provide Islamic investors with Shariah-compliant versions of a wide variety of popular benchmarks. # MJ SSIM VI(II) & VII (I) 4, 2014 Volume VI / VII, Issue II / I SuGyaan 47 Volume VI / VII, Issue II / I SuGyaan 48 Volume VI / VII, Issue II / I SuGyaan 49 Volume VI / VII, Issue II / I 50 SuGyaan Impact of Inflation on Economic Factors in Indian Economy *Dr.Meenakshi Tyagi and **Renu Sharma Abstract When economic development process starts it brings the quantitative and qualitative changes in the multiple areas of an economy like development of human capital, critical infrastructure, saving and investment, regional competitiveness, environmental sustainability, social inclusion, health, safety, literacy, and other initiatives. But on the other hand, economy has to bear the inflationary pressures during the process of development. Indian economy also finds its name in the list of developing economies that is why for a fairly longer period of time Indian economy has been fighting with the problem of inflation because of increasing demand put forward by uncontrolled population, low growth rate in agro products, investment in long gestation projects, hoardings and black money. From time to time Indian government has been using various monetary and fiscal measures to control the inflation but all went in vein and still inflation is hampering Indian economy. The present study shows the impact of inflation on economic factor and examines the inter- relationship between economic growth, investment and household saving rate through various statistical tools like correlation, regression and t-test. To accomplish the purpose past 12 years data have been taken. The result shows that Inflation has a negative effect on growth but positive effect on investment and household savings. Due to the unavailability of required secondary data the research is limited to few economic factors. Still these findings for Indian economy with widely divergent values of aggregates are very relevant for development policies and strategies. Keywords: Economic development, Inflation, Investment, Household Savings, GDP JEL Classification Code : E60 Introduction In developing nations Economic development brings the quantitative and qualitative changes in the economy which includes multiple areas, like development of human capital, critical infrastructure, saving and investment, regional competitiveness, environmental sustainability, social inclusion, health, safety, literacy, and other initiatives. During the development process, huge investment is made to develop social overhead capital (SOC) which generates a smooth path for direct productive activities (DPA). Because of long gestation period of SOC, an economy has to bear the inflationary pressures during the process of development. The impact of inflation can be seen in each and every area of an economy when development process starts. But if inflation continues to rise in long run, it has negative impact on growth rate. Inflation is a rise in the general level of prices of goods and services in an economy over a period of time. When the general price level rises, each unit of currency buys fewer goods and services. Consequently, inflation also reflects erosion in the purchasing power of money – a loss of real value in the internal medium of exchange and unit of account in the economy.Inflation impacts every citizen of a country. It also leads to reduction in investors’ confidence in the economy due to price uncertainty. So, RBI strives to maintain a moderate level of inflation that is good for the economy. A chief measure of price inflation is the inflation rate, the annualized percentage change in a general price index (normally the consumer price index over time). Many developing countries use changes in the Consumer Price Index (CPI) as their central measure of inflation. Consumer Price Index or CPI measures the average prices of goods and services that we, the consumers, have paid for. There are 8 groups in which CPI is used. They are: education, apparel, foods and beverages, communication, transportation, recreation, housing, and medical care. Other services like school and government registration fees and electricity and water bills are sometimes counted aswell. *Assistant Professor, MBA Deptt, KIET, Ghaziabad, [email protected], [email protected], Address- 3/ 1228, vasundhara, Ghaziabad, (U.P.), PIN-201012, Mobile- 9540806623.; **Assistant Professor, MBA Deptt, KIET, Ghaziabad, [email protected], Address- B-9,Krishanpura, Modinagar (U.P.), Pin- 201204, Mobile- 7500149806. Volume VI / VII, Issue II / I 51 SuGyaan However, this method is unsuitable for use in India, for structural and demographic reasons. CPI numbers are typically measured monthly, and with a significant lag, making them unsuitable for policy use. This is why the Wholesale Price Index, is used to measure inflation rate in India. Now since September 2010 with the introduction of new base year 2004-05, each week the wholesale price of a set of 676 goods is calculated by the Indian government. The WPI measures the price of a representative basket of wholesale goods. In India, this basket is composed of three groups: Primary Articles (20.1% of total weight), Fuel and Power (14.9%) and Manufactured Products (65%). Food Articles from the Primary Articles Group account for 14.3% of the total weight. The most important components of the Manufactured Products Group are Chemicals and Chemical products (12%); Basic Metals, Alloys and Metal Products (10.8%); Machinery and Machine Tools (8.9%); Textiles (7.3%) and Transport, Equipment and Parts (5.2%). The inflation rate in India was recorded at 8.79 percent in January of 2014. Inflation Rate in India averaged 9.83 Percent from 2012 until 2014, reaching an all time high of 11.16 Percent in November of 2013 and a record low of 7.55 Percent in January of 2012. These days economies of all countries whether underdeveloped, developing as well developed suffers from inflation. Inflation or persistent rising prices are major problem today in world. Because of many reasons, first, the rate of inflation these years are much high than experienced earlier periods. Second, Inflation in these years coexists with high rate of unemployment, which is a new phenomenon and made it difficult to control inflation. The Indian economy has been registering stupendous growth after the liberalization of Indian economy. In fact, till the early nineties Indians were used to ignore inflation. But, since the mid-nineties controlling inflation has become a priority. The natural fallout of this has been that we, as a nation, have become virtually intolerant to inflation. The opening up of the Indian economy in the early 1990s had increased India’s industrial output and consequently has raised the India Inflation Rate. While inflation was primarily caused by domestic factors (supply usually was unable to meet demand, resulting in the classical definition of inflation of too much money chasing too few goods), today the situation has changed significantly. Inflation today is caused more by global rather than by domestic factors. Naturally, as the Indian economy undergoes structural changes, the causes of domestic inflation too have undergone tectonic changes. The main cause of rise in the rate of inflation rate in India is the pricing disparity of agricultural products between the producer and consumers in the Indian market. Moreover, the sky-rocketing of prices of food products, manufacturing products, and essential commodities have also catapulted the inflation rate in India. Furthermore, the unstable international crude oil prices have worsened the situation. High prices of day-to-day goods make it difficult for consumers to afford even the basic commodities in life. This leaves them with no choice but to ask for higher incomes. Hence the government tries to keep inflation under control. Literature Review In the literature of inflation, the most attention has been paid to maintain an appropriate rate of inflation which could have a favourable impact on macro economic factors, required for a smooth growth rate in an economy. Inflation affects numerous macroeconomic factors economic growth rate, savings, investment, employment, foreign exchange rate, etc. The rate of these factors is widely varying across the nations and so also their economic growth. The effect of inflation on savings, however, is ambiguous both in theory and practice (Heer and Suessmuth, 2006; and Deaton and Paxson, 1993). This is why the relationship between inflation and growth remains a controversial. Originating in the Latin American context in the 1950s, the issue has generated an enduring debate between structuralistsand monetarists. The structuralists believe that inflation is essential for economic growth, whereas the monetarists see inflation as detrimental to economic progress. Empirical Volume VI / VII, Issue II / I SuGyaan evidence about the relationship of inflation and growth also differs with some studies finding a negligible effect of inflation on growth (e.g. Chari et al., 1996), some finding a negative effect (Chopra, 1988; Fischer, 1993; Gylfason and Herbertsson, 2001) and some studies providing an evidence of positive effect (Dholakia, 1995; Mallik and Chowdhury, 2001). The effect of inflation on economic growth in theory is largely through the sub-optimal use of resources and distorted investment decisions due to inflation (Miller and Benjamin, 2008; Paul et. al., 1997). However, it is also found in practice that economic growth is also led by inflation. On the other hand, higher growth can lead to reduced inflation. (Dholakia R. H., 1990). Thus, the relationship between growth and inflation may also be bidirectional. This ambiguous relationship between inflation and growth implies that though rising inflation may have associated growth costs, policy efforts to contain inflation could negatively affect growth. On the other hand, allowing inflation at higher rates could lead to higher growth although it may cause some distorted choices. Relationship between inflation and savings is critical in understanding this complex trade-off between growth and inflation particularly for the policy makers. There are broadly two types of theoretical expectations concerning the effect of change in average inflation level on output growth (Chari et al., 1996). One expectation, based on exogenous growth models, is that inflation rate will have no effect on the growth rate as well as the level of output. As opposed to this, the endogenous growth models emphasize that money and inflation do affect the growth rate of output itself. There are two channels for such an effect. One argument is known as the Mundell-Tobin effect in which a more inflationary policy enhances growth as investors move out of money and into growth enhancing capital investment. This is because inflation reduces the wealth of people, and for accumulating the desired wealth, people save more, decreasing real interest rate and driving up capital accumulation (Haslag, 1997). It is possible, however, to argue that inflation in such a case would affect savings and investment decisions essentially by increasing the 52 uncertainties with regard to the real rates of return. This can actually reduce the productive capital and hurt the output growth (Motley, 1994; and Miller and Benjamin, 2008). Growth, savings, investment, employment and inflation are interrelated variables and should, therefore, be endogenously determined simultaneously in the system. However, most of the studies on these variables do not analyze them in a simultaneous equation framework. It is important for a policy maker to understand the dynamics among economic growth, savings and inflation in the system. If inflation increases, it also raises the consumption expenditure which results in low household savings. The effect of inflation on savings depends on the way households react to increase in inflation (Chopra, 1988). If households direct their savings from financial to physical assets and consumer durables, then due to increase in consumption of consumer durables, present savings will decline. Most of the studies examining the relationship between inflation and growth end up focusing on the effect of inflation on savings and investments and thereby on the growth of the economy, assuming independence of the incremental capital output ratio (ICOR) from inflation. Except Chopra (1988), the ICOR channel of the effect of inflation on growth is not seriously examined in the literature. Thus, if inflation leads saving rate to increase and ICOR to decrease, inflation will definitely promote growth, but the reverse would be true if saving ratio decreases and ICOR increases with inflation. If both these variables increase or decrease simultaneously as a result of inflation, the magnitude of the statistical impact of inflation on these two variables would determine the sign of the relationship between inflation and growth. Chopra (1988) argued that inflation would affect the ICOR by changes in the composition of output produced as a result of households shifting from financial savings to physical savings or consumer durables in an economy. This would lead to shifts of investment from low capital intensive industries to high capital intensive industries, increasing the capital output ratio in the economy. Thus, inflation is likely to increase the ICOR. Volume VI / VII, Issue II / I SuGyaan Also, due to increased uncertainty, the utility from holding wealth declines leading to increased consumption and decreased savings. On the other hand, wealth owners interested in maintaining the real value of their wealth would increase their savings in an inflationary scenario to maintain the desired amount (Chopra, 1988). Most of the models analyzing the effect of inflation on savings find a considerably negative effect (Heer and Suessmuth, 2006). If the incomes are not indexed, unanticipated inflation will cause unanticipated cuts in the real income and hence decreased the saving rates (Deaton, 1977). Also, high inflation can increase the opportunity cost of holding money and increase the rewards for the search activities in shopping wasting real resources and thereby reducing savings (Miller and Benjamin, 2008). As against this, another theory proposes that if the real income is correctly anticipated either by indexation or wage inflation, unanticipated inflation will increase the saving rate. Inflation is a good proxy for macroeconomic uncertainty. Higher uncertainty induces people to save a larger portion of their money for precautionary motives. Thus rise in inflation should have a positive coefficient. Savings will also increase if there are lifecycle factors promoting savings (Deaton and Paxson, 1993). (Heer and Suessmuth, 2006) have stated that if one believes in the super-neutrality of money in the ultimate sense, inflation cannot have any effect on savings in the long run The impact of inflation on growth, output, investment, employment and productivity has been one of the main issues examined in macroeconomics. Theoretical models in the money and growth literature analyze the impact of inflation on growth focusing on the effects of inflation on the steady state equilibrium of capital per capita and output (e.g., Orphanides and Solow, 1990). There are three possible results regarding the impact of inflation on output and growth: i) none; ii) positive; and iii) negative. Sidrauski (1967) established the first result, showing that money is neutral and superneutral1 in an optimal control framework considering real money balances (M/P) in the utility function. Tobin (1965), who assumed money as substitute 53 to capital, established the positive impact of inflation on growth, his result being known as the Tobin effect. The negative impact of inflation on growth, also known as the anti-Tobin effect, is associated mainly with cash in advance models (e.g., Stockman, 1981) which consider money as complementary to capital. Based on cross-country and panel regression, several studies have demonstrated in recent years, that there is negative correlation between inflation and growth in the long run due to the influence of the former on reducing investment and productivity growth. Earlier works (for example, TunWai, 1959) failed to establish any meaningful relationship between inflation and economic growth. A work by Paul, Kearney and Chowdhury (1997) involving 70 countries (of which 48 are developing economies) for the period 1960-1989 found no causal relationship between inflation and economic growth in 40 % of the countries; they reported bidirectional causality in about 20 % of countries and a unidirectional (either inflation to growth or vice versa) relationship in the rest. More interestingly, the relationship was found to be positive in some cases, but negative in others. Recent cross-country studies, found that inflation affecting economic growth negatively, includes Fischer (1993), Barro (1996) and Bruno and Easterly (1998). Fischer (1993) and Barro (1996) found a very small negative impact of inflation on growth. Yet Fischer (1993: 281) concluded ¯however weak the evidence, one strong conclusion can be drawn: inflation is not good for longer-term growth . Barro (1996) also preferred price stability because he believed it to be good for economic growth. The effect of macroeconomic instability on growth comes largely from the effect of uncertainty on private investment. Multi-country panel data studies on investment report that measures of macroeconomic instability, like the variability in the real exchange rate or the rate of inflation, have an adverse impact on investment (Serven and Solimano 1992). Fischer (1993) examines the role of macroeconomic factors in growth. He found evidence that growth is negatively associated with inflation and positively associated with good fiscal performance and undistorted foreign exchange markets. Growth may be linked to Volume VI / VII, Issue II / I 54 SuGyaan uncertainty and macroeconomic instability where temporary uncertainty about the macro economy causes potential investors to wait for its resolution, thereby reducing the investment rate (Pindyck and Solimano 1993). The Chakravarty Committee (RBI, 1985) referred to an inflation rate of 4 % as an acceptable rise in prices. This can be regarded as the first influential fix on the threshold rate of inflation in India. More recent studies have made estimates of threshold inflation using Sarel methodology and these estimates place threshold inflation for India in the range of 4-7 % (Kannan and Joshi, 2002; Rangarajan, 1997; RBI, 2003a; Samantaraya and Prasad, 2001; Vasudevan, Bhoi and Dhal, 1998). The estimate of threshold inflation has, however, a shifting perspective (RBI, 2003b). With structural changes in the economy, prolonged price stability at the global level as well as in India and the credible anchoring of inflationary expectations at a lower level, the threshold inflation could also move downwards. makers to make appropriate economic policies to set a smooth path for swift growth of Indian economy. Hypotheses The following three Alternative Hypotheses have been framed: 1. Hα: High inflation slows down growth rate. 2. Hα: Inflation accelerates investment rate in DPA. 3. Hα: Inflation curtails household savings. Research Design To examine the impact of inflation on GDP, Employment, Saving, Investment, Import and Export, Secondary data of past ten years have been comprised from various sources. In order to analyze the data tabulation, correlation and regression have been used. Interrelationship between Inflation and Economic Factors Objective of the Study Economists also advocate a moderate rate of inflation for economic growth of a nation and 5Inflation influences each and every area of an 6% rate is considered good for an economy. But if economy. The main objective of this paper is to this rate goes up, it becomes obstacle in the examine the impact of Inflation on various economic growth of the nation. The present study economic factors i.e. Growth rate, Saving, tries to seek the relationship between inflation, Investment, Employment, Import and Export. To GDP and the related factors, as it is said a moderate make the study more precise, it attempts to show rate of inflation has positive impact on growth, the interrelationship between inflation, GDP, investment and direct productive activities. (Table Investment and Household savings. This 1) relationship can provide a better way to policy Table 1 Macro Economic Indicators Time GDP Inflation WPI Inflation CPI Industry GDP growth 2002-03 3.88 3.4 4.1 7.21 2003-04 7.97 5.5 3.8 7.32 2004-05 7.05 6.5 3.9 9.81 2005-06 9.48 4.4 4.2 9.72 2006-07 9.57 6.5 6.8 12.17 2007-08 9.32 4.82 6.2 9.67 2008-09 6.72 8 9.1 4.44 2009-10 8.59 3.6 12.3 9.16 2010-11 8.91 9.6 10.5 7.55 2011-12 6.69 8.8 8.4 7.81 2012-13 4.47 7.4 10.2 0.96 2013-14 4.86 6.5 9.6 0.65 Source: CMIE Volume VI / VII, Issue II / I 55 SuGyaan Table 2 Savings & Investiments Time Savings Investment Household savings 2002-03 25.93 25.02 21.2 2003-04 29.03 26.17 22 2004-05 32.41 32.45 23.1 2005-06 33.44 34.28 23.5 2006-07 34.6 35.87 23.15 2007-08 36.82 38.11 22.42 2008-09 32.02 35.53 23.64 2009-10 33.69 36.3 25.18 2010-11 34.02 36.53 23.51 2011-12 31.81 36.39 22.33 2012-13 31.8 34.7 22.8 2013-14 Source: CMIE 30.5 35.3 24 Table 3 Unemployment, Export & Import Growth Time Unemployment Export Growth Import Growth 2002-03 - 20.36 14.56 2003-04 - 23.23 24.03 2004-05 5.5 28.51 48.63 2005-06 5.1 23.47 32.13 2006-07 4.6 20.36 21.39 2007-08 4.6 23.23 35.08 2008-09 5.8 28.51 19.76 2009-10 9.3 23.47 -2.56 2010-11 9.6 20.36 26.78 2011-12 8.9 23.23 31.07 2012-13 8.1 28.51 0.54 2013-14 7.4 23.47 -6 Source: CMIE Data Analysis The above mentioned Data have been analyzed by using Karl Pearson correlation and regression techniques. It gives following results : As we all know that a certain rate of inflation is required for the smooth growth rate of an economy but if it continues increasing beyond that rate then it starts impeding the growth rate. The regression equation is GDP = 7.53 - 0.038 WPI Predictor Coef SE Coef Constant 7.527 2.104 3.58 0.005 -0.0375 0.3219 -0.12 0.909 WPI T p-value Pearson correlation and regression analysis also support the same but p value (0.909) is much higher than 0.05 (.909 > 0.05) which shows that relationship between two variables is not Volume VI / VII, Issue II / I 56 SuGyaan significant and that is why first Há is rejected. On the other hand, when rate of inflation goes up it increases the induced investment. Induced investment is that investment which changes with the change in income of the rate of profit. It increases with as income increases and decreases as income decreases. Thus-induced investment is income elastic. The induced investment curve slopes upward to might showing increase in investment as a result of increase in income. Autonomous investment, on the other hand, is independent of income and is not guided by profit motive. This investment is generally undertakes by the Government, who is not guided by the profit consideration. The autonomous investment curve is a horizontal straight line parallel to the OX-axis. It indicates that the investment remains the same at all levels of income. In equation form investment can be defined as: I= a+ bY Where, I= Aggregate investment, a is constant means autonomous investment and b is induced investment which depends on income (Y).In present study we find the regression equation of investment on inflation is: Investment = 28.5 + 0.861 WPI Predictor Coef SE Coef T p-value Constant 28.504 3.894 7.32 0.000 WPI 0.8611 0.5959 1.45 0.179 Pearson correlation is 0.416; it shows a moderate degree positive correlation between investment and inflation WPI. But p value (0.179) is higher pace of economy growth slower and somehow it affects it negatively. Second, household savings fall but overall savings not. Inflation has positive impact on investments. These findings can have important policy implications. The important conclusion is that any increase in inflation from the previous period negatively affects growth this is why the policymakers should note that any increase in inflation from the previous period at than 0.05 (0.179 > 0.05) which shows that relationship between two variables is not significant and that is why second Há is also rejected. As it is said that during inflation because of higher prices consumers are left with less savings this in turn decreases the share of household savings in total savings. By analyzing the data we find: The regression equation is Household savings = 22.9 + 0.028 WPI Predictor Coef SE Coef T p-value Constant 22.895 1.071 21.38 0.000 WPI 0.0278 0.1639 0.17 0.869 Here, Pearson correlation shows low degree positive relationship between inflation and household savings. It does not support third H1; the reason is because inflation affects different segments of society differently. In this case p value (0.869) is higher than 0.05 (0.869 > 0.05) which shows that relationship between two variables is not significant and that is why third Há is also rejected. To see the impact of growth, investment and savings on inflation multivariate regression has been used and the summary is as follows: Conclusion As economics states that inflation affects different sections of economy differently, some sections are benefited while some are affected adversely. The positive impact of inflation is, it is beneficial for producers who play crucial role in an economy. If this section has large gains, results in higher investment, higher production, higher employment and higher growth rate. As the main objective of this paper was to examine the interrelationship between inflation and economic growth, investment, employment, savings, imports and exports. The interesting results found in this exercise are that the inflation makes the Model Summary Model 1 R .522 R Square a .273 Adjusted R Std. Error of the Square Estimate .000 1.98796 a. Predictors: (Constant), investment, growth, savings Volume VI / VII, Issue II / I 57 SuGyaan ANOVAb Model Sum of Squares Df Mean Square F Sig. Regression 11.856 3 3.952 1.000 .441a Residual 31.616 8 3.952 Total 43.472 11 a. Predictors: (Constant), investment, growth, savings b. Dependent Variable: WPI Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. .581 .577 B Std. Error Beta (Constant) 6.131 10.557 growth .108 .604 .110 .179 .862 savings -.541 .764 -.765 -.709 .499 investment .494 .377 1.024 1.312 .226 a. Dependent Variable: WPI The regression equation is WPI = 6.1 + 0.108 Growth - 0.541 Savings + 0.494 Investment Regression Analysis: CPI versus Growth, Savings, Investment, Household savings and Exports The regression equation is CPI = - 27.4 - 0.667 Growth - 0.213 Savings + 0.510 Investment + 1.50 Household Savings - 0.227 Exports Predictor Coef SE Coef T P Constant -27.36 22.16 -1.23 0.263 Growth -0.6669 0.8422 -0.79 0.459 Savings -0.2133 0.9785 -0.22 0.835 Investment 0.5097 0.5078 1.00 0.354 Household Savings 1.5028 0.8853 1.70 0.141 Exports -0.2274 0.2635 -0.86 0.421 S = 2.07446 R-Sq = 73.7% R-Sq(adj) = 51.9% Analysis of Variance Source Regression Residual Error Total DF 5 6 11 SS 72.502 25.820 98.322 Source Growth Savings Investment Household Savings Exports DF 1 1 1 1 1 Seq SS 0.466 28.450 30.920 9.462 3.204 MS 14.500 4.303 F 3.37 P 0.086 Volume VI / VII, Issue II / I 58 SuGyaan any level has negative effect on economic growth. However, the fact that the common people and the decision makers do not like inflation has enormous effects on the consumption pattern, which in turn affects the output demanded. Macroeconomic stability and the necessary infrastructure are among the preconditions for sustained growth. Among the ways inflation can affect growth, an important avenue is the effect of inflation on investment. Low or moderate inflation is an indicator of macroeconomic stability and creates a favourable environment for investment. Countries with moderate rates of inflation have higher growth rates over the longterm compared with countries with high inflation rates. The Indian experience appears to support the above view. In India, government also needs to make the effective monetary policy so that inflation could be kept under control. To promote growth and keep inflation at moderate level, the government needs to control budget deficits. This can be achieved by switching public expenditure from consumption to investment, this may be difficult to pursue, especially in a developing country where parallel economy is existing with a multiparty democracy but this is the urgent need of Indian economy. Indian government should curtail unproductive expenditure, which is a cause of high inflation rate and low growth rate. To maintain sustainable growth,government also needs to make induced investments to promote new technologies and innovations to increase level of production that can help Indian economy to restart the engine of growth. References 1. Andres J. and I. Hernando (1997). Does inflation harm Economic Growth? Evidence for the OECD, Banco de Espana Working Paper 9706. 2. Athukorala, P. C. and Sen, K. (2004) The Determinants of Private Saving in India. World Development, Vol. 32, No. 3, pp. 491– 503 3. Balakrishnan P (2005): ¯Macroeconomic policy and economic growth in the 1990s”, Economic and Political Weekly, XXXX, 39693977. 4. Barro ,R. and Sala-i-Martin, X. 1995. Economic Growth. McGraw Hill 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. Barro, R. J. (1995). Inflation and economic growth. NBER Working Paper 5326. Cambridge, Bruno, M.,&Easterly,W. (1998). Inflation crises and long-run growth. Journal of Monetary Economics, 41, 3–26. Chakravarty Committee (RBI report 1985) Charan D Wadhava [ed.] (1978), Some problems of India’s Economic Policy, Tata McGraw-Hill, New Delhi. Chopra, S. 1988. Inflation, Household Savings and Economic Growth. Ph. D. thesis, M. S. University of Baroda, India. Dholakia, Archana. 1990. Benefits from Government Expenditures in India- A Welfare Indicator Approach. Bombay: Himalaya Publishing House, India. Dholakia, R. H. 1990. Extended Phillips Curve for the Indian Economy. Indian Economic Journal, Vol. 38, No. 1, pp. 69-78. Dholakia, R. H. 1995. Expected Inflation and Short-Term Forecast of Growth Rate in India. IASSI Quarterly, Vol. 13, No. 4, pp. 44-67. Fischer, S (1993): ‘The Role of Macroeconomic Factors in Growth’, Journal of Monetary Economics, Vol 32(3). Khan, M. S. and Senhadji, A. S. 2001. Threshold Effects in the Relationship Between Inflation and Growth. IMF Staff Papers 2001, Vol. 48, No. 1. Krishnamurty K (2002): “Macroeconomic models for India: past, present and prospects”,Economic and Political Weekly, XXXVII, No 42 (October 19). K Krishnamurty, ‘Inflation and Growth: A Model for India’ in Krishnamurty and Pandit, Macro Econometric Modeling of the Indian Economy, (Hindustan Publishing Corporation, 1985) pp 39-42. Mallik, G. and Chowdhury, A. 2001. Inflation and Economic Growth: Evidence from four South Asian Countries. Asia-Pacific Development Journal Vol. 8, no. 1, June 2001. Smyth, D. J. (1994), “Inflation and Growth”, Journal of Macroeconomics 16: 261-270. #MJ SSIM VI(II) & VII (I) 5, 2014 Volume VI / VII, Issue II / I 59 SuGyaan Book Review THE CHALLENGES OF INDIAN MANAGEMENT Author: Prof.B.R.Virmani Publisher: Response Books; A division of Sage Publication Indian Private Limited, First published in 2007, ISBN: 9780761935513. Reviewers: Dr.Pavan Patel, Professor and Mr.K.V.S.Krishnamohan, Associate Professor, SSIM, Kompally, Secunderabad. 500014. Author: Professor B.R Virmani is the founder Chairman, Centre for Organisational Research &Development in Management (CORD-M) Hyderabad, India. Professor BR Virmani has been the Dean and IPCL Chair Professor of Strategic Management at Administrative Staff College of India (ASCI). He is Academic Advisory Board Member of Siva Sivani Institute of Management. Secunderabad, Andhra Pradesh. Professor Virmani has published over 50 articles and 14 books, including Managing People in Organization’s: Challenges of Change; Indian Management; Evaluating Management and Development; Participative Management vs. Collective Bargaining; Workers Education; Economic Development Alternatives: Andaman and Nicobar Island; Economic Restructuring, Technology Transfer and Human Resource Development etc. His latest book on The Challenges of Indian Management address the burning issues in Indian Organizational Management Practices and divided the contents into five parts, the first part consist Indian Management: An Overview, the chapter focus on the universality of management versus culture specificity further this chapter elaborated on practice of Indian Management from historical perspective. Second part consists: Indian management through the ages, brief about Vedic period administrative structure, Kautilya model of administrative setup and management practices, Aryan period, and British period and discussed further up to the period of postIndependence period. This part also includes Management outside India, focusing more on development of Management practices in Western world discussing from Scientific Management to Business Process Re-engineering, Total Quality Management and 360degrees feedback etc. At the same time the author highlighted Japanese Management also. Third Part consists the working of Indian Management typical cases for the study purpose the author has taken five different types of organizations which includes a government department, a public sector, a traditional familyowned Indian Organization, a traditional British multinational and American information technology based organization. This study focused on the similarities of management practices and similarity in differences. Part four discussed on Indian Management Practices: Employees Perspective, study conducted through a structured questionnaire employee perspective on Indian Management practices this concludes very interesting facts about the Indian management practices. Part fifth chapter number seven explaining what is Indian Management and comparative management practices in the west, japan and India, mentioned very clearly to understand gap between execution management in India and claimed the management practice. This will enhance readers to understand that the importance of execution management in the organization to accomplish the objectives of the organization. In the last chapter the author concluded that the Indian organizations can fallow the foreign systems of management provided that those have adaptive and modified to the Indian climate to be effective in accomplishing the organizational objectives. This book recommended highly for business leaders, HR and OD consultants, Management experts, and as an additional reading for Volume VI / VII, Issue II / I SuGyaan management students in the subjects like Human Resource Management, Organizational Development, and Strategic Human Resource Management. Interesting aspect here would be the irrespective of nature of business leader can understand the pulse of employees perception towards management, further this book will help business leaders bring a all-inclusive change in the business organization irrespective of nature of organization. 60 Specifically for Academicians each chapter in this book will help as a case study for covering respective topics in the area of almost major functional areas of management, how Indian management challenges can be understood, it can be solved adopting, modified, improvised western management practices and concepts applied in Indian scenario to address the challenges. #MJ SSIM VI(II) & VII (I) 6, 2014 Volume VI / VII, Issue II / I SuGyaan 61 Siva Sivani Institute of Management S.P Sampathy’s Siva Sivani Institute of Management is promoted by the Siva Sivani Group of Educational Institutions, which has been running the prestigious and internationally renowned Siva Sivani Public Schools for more than four decades. Approved by the All India Council for Technical Education, Ministry of Human Resource Development, Government of India, New Delhi, Siva Sivani Institute of Management started functioning as an autonomous institute in 1992. Located in Secunderabad, far from the maddening crowd, about 6 Km. from Bowenpally along the National Highway No.7, Siva Sivani Institute of Management has an enviable environment - serene, spacious and stupendous. It offers an ideal environment for imparting value- based management education. The Institute designs and updates courses at any given point of time, even if it is in the middle of an academic year or a term for that matter. Stalwarts from both the industry and the academia constantly provide inputs for fine tuning the course curriculum to meet the needs of the industry. SSIM is consistently ranked amongst the top Business Schools in the country. Currently, SSIM is ranked 35th in the country amongst the B-Schools of Excellence as per Business Barons Survey March 2009. The other Group Institutions are: Siva Sivani Global Centre for HR Excellence, Siva Sivani Institute of Global Studies, Siva Sivani Man Management Private Limited and Siva Sivani Degree College. Siva Sivani Institute of Management offers four PGDM Programmes: The PGDM (Triple Specialization) This program prepares a student towards building multifaceted functionality. PGDM (TPS) is designed in such a way that has evolved from the needs of the industry, which is continually looking for managers with cross functional skills embedded and supported by IT savvy acumen. A student of PGDM (TPS) has a major specialization one of Finance/Marketing/HR/System along with one of the specialization art of Finance, Marketing, HR, System, Operations as minor specialization and also elective courses like Finance, Human Resources and Marketing, ERP, electives such as Retail Management, Banking, Event Management, BPO Management, Insurance Management etc. PGDM (Marketing) This is a highly specialized two year management programme in Marketing. This programme is completely tailor made to the requirements of industry with respect to marketing. PGDM (HR) with IT This is highly specialized programme in HR along with IT focus. The latest and global concepts in the area of HR that includes compensation management, Psychometrics HR audit, Negotiating skills, Managing diversity etc. PGDM (Banking, Insurance, Finance and Allied Services) This programme encompasses all the finance related areas and we have included Banking and Insurance sectors as specializations in addition to core Finance. All the latest topics in Banking and insurance have been included and to name the few are Risk management in Banks, Technology management in Banks, Claims management in insurance, Actuarial science etc PGDM (Global Business) Siva Sivani offers a highly specialized program – PGDM in Global business. The world is fast becoming a global village and there is a huge demand for students who are multi skilled and who can transfer their skills and expertise seamlessly across countries and continents. This well thought out and executed course with a through exposure to global thoughts and latest global practices will equip the students to become truly global managers. Volume VI / VII, Issue II / I Please tear it off from here  Rates of Annual Subscription For Instituions (Two Issues) Rs. 500/All Correspondences relating to Subscription may be addressed to Asst. Editor Siva Sivani Institute of Management NH-7, Kompally, Via-Hakimpet, Secunderabad-500014 Phones: 040-65457236, 65457237, 040-27165450-54 Fax No.040-27165452 www.ssim.ac.in Subscription Order From (Give Full Mailing Address) To Asst. Editor Siva Sivani Institute of Management NH-7, Kompally, Via-Hakimpet, SECUNDERABAD-500014 Sir/Madam, Please find enclosed a DD for Rs. ..................................... (in words ................  ............................................................. only) DD No. ..................... dt....................... from .......................................................... Bank. Drawn in favour of “Siva Sivani Institute of Management, Secunderabad” being Annual Subscription for 20 . Signature Call for Papers Dear Author/s, SuGyaan is a medium for keen researchers to publish their unpublished research findings that are of interest to academic community and industry. It is also a medium for industry professionals to share their best practices. The journal encourages publication of application of theory to real life management activities Editorial Advisory & Review Panel: Eminent persons from the academic community and industry are guiding the journal in its Endeavour. Professors from reputed institutions from India and abroad are members of the review panel. Frequency: The Journal is published bi-annually in the months of July and December. Content Mix: The journal prefers to publish conceptually sound and methodologically rigorous papers that advance the body of knowledge. The journal would publish Empirical Research Findings, Conceptual Papers, Literature Reviews, Case Studies, Synopsis of Doctoral Theses and Book Reviews, summaries of Ph.D. thesis, roundtable of academicians, policymakers, industry experts on any topic relevant to present business scenario and articles on contemporary business issues. Review Process: SuGyaan is a referred journal. All manuscripts submitted for publication would be screened by the editor for relevance to our journal. Appropriate manuscripts would be put through ‘double blind review process’ that may normally take four to eight weeks. Accepted manuscripts may be edited to suit the journal’s format. Wherever possible reviewer’s feedback will be provided. However the journal has no binding to provide detailed feedback in every case including the contributions rejected. Copyright: Published manuscripts are exclusive copyright of SuGyaan, Management, Journal of Siva Sivani Institute of Management. The copyright includes electronic distribution as well. Format and Style: • Articles should not exceed 10000 words (10-15 A-4 size pages, typed in double space) including charts, tables and other annexure. • An abstract not exceeding 150 words should be included in the beginning of the paper with Key words and JEL Classification Code. • Manuscripts should be submitted in duplicate. • Author’s name, designation, official address etc., should be mentioned only on the cover page. Author’s identity should not be mentioned anywhere else in the paper. • Only those sources that are cited in the text should be mentioned. 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